Title of Invention

METHOD OF ENCODING AND DECODING FOR AUDIO SIGNALS USING COMPLEX VALUED FILTER BANKS

Abstract

An encoder (109) comprised a receiver(201) which receives a time domain audio signal. a filter bank(203) generates a first subband signal from the domain audio signal where the first subband signal corresponds to a non-critically sampled complied generates domain representation of the time domain signal. A conversion processor (205) generates a second signal from the first subband signal by subband processing. The second subband signal corresponds to a critically sampled subband domain representation of the time domain audio signals. An encode processor (207) then generates a waveform encoded data stream by encoding data values of the second subband signal. The conversion converting back to the time domain. The invention allows an oversampled subband signal typically generated in parametric encoding to be waveform encoded with reduces complexity. The decoder performes the inverse operation.

Full Text

ENCODING AAND DECODING OF AUDIO SIGNALS USING COMPLEX-VALUED FILTER BANKS The invention relates to encoding and/or decoding of audio signals and in particular to waveform encoding/decoding of an audio signal. Digital encoding of various source signals has become increasingly important over the last decades as digital signal representation and communication increasingly has replaced analogue representation and communication. For example, mobile telephone systems, such as the Global System for Mobile communication, are based on digital speech encoding. Also distribution of media content, such as video and music, is increasingly based on digital content encoding. Traditionally, audio encoding has predominantly used waveform encoding wherein the underlying waveform has been digitized and efficiently encoded. For example, a typical waveform encoder comprises a filter bank converting the signal to a frequency subband domain. Based on a psycho-acoustical model, a masking threshold is applied and the resulting subband values are efficiently quantized and encoded, for example using a Huffman code. Examples of waveform encoders include the well known MPEG-1 Layer 3 (often referred to as MP3) or AAC (Advanced Audio Coding) encoding schemes. In recent years, a number of encoding techniques have been proposed which do not directly encode the underlying waveform but rather characterizes the encoded signals by a number of parameters. For example, for voice encoding, the encoder and decoder may be based on a ;■ odel of the human voice tract and instead of encoding the waveform, various parameters and excitation signals for the model may be encoded. Such techniques are generally referred to as parametric encoding techniques. Furthermore, waveform encoding and parametric encoding may be combined to provide a particularly efficient and high quality encoding. In such systems, the parameters may describe pail of the signal with reference to another part of the signal which has been waveform encoded. For example, coding techniques have been proposed wherein the lower frequencies are waveform encoded and the higher frequencies are encoded by a parametric extension that describes properties of the higher frequencies relative to the lower frequencies. As another example, multi-channel signal encoding has been proposed wherein e.g. a mono signal is waveform encoded and a parametric extension includes parameter data indicating how the individual channels vary from the common signal. Examples of parametric extension encoding techniques include Spectral Band Replication (SBR), Parametric Stereo (PS) and Spatial Audio Coding (SAC) techniques. Currently the SAC technique is being developed to efficiently code multichannel audio signals. This technology is partly based on the PS coding technique. Similarly to the PS paradigm, SAC is based on the notion that a multi-channel signal, consisting of M channels, can be efficiently represented by a signal consisting of N channels, with N Like the SBR and PS techniques, SAC uses complex (pseudo) Quadrature Mirror Filter (QMF) banks in order to transform time domain representations to frequency domain representations (and vice versa). A characteristic of these filter banks is that the complex-valued sub-band domain signals are effectively oversampled by a factor of two. This enables post-processing operations of the sub-band domain signals without introducing aliasing distortion. Another common characteristic for parametric extensions is that under typical conditions, these techniques do not achieve a transparent audio quality level, i.e. that some quality degradation is introduced. In order to extend the parametric extensions like SBR, PS and SAC towards transparent audio quality it would be desirable to code certain parts, e.g. a certain number of bands, of the complex sub-band domain signals using a waveform coder. A straightforward approach consists of first transforming these parts of the complex sub-band domain back to the time domain. An existing waveform coder (e.g. AAC) can then be applied to the resulting time domain signals. However, such an approach is associated with a number of disadvantages. Specifically, the resulting encoder and decoder complexity is high and has a high computational burden because of the repeated conversions between the frequency and time domain using different transforms. For example, if the parametric extension would make use of coding the time domain signal obtained after QMF synthesis, the corresponding particular, a synthesis filter bank may be used both for decoding a parametric extension for the time domain audio signal and for waveform decoding. A commonality between waveform decoding and parametric decoding can be achieved. In particular, the synthesis filter bank can oe a QMF filter bank as typically used for parametric decoding in parametric extension coding techniques such as SBR, PS and SAC. The conversion processor is arranged to generate the second subband signal by subband processing without requiring any conversion of e.g. the first subband signal back to the time domain. The decoder may further comprise means for performing non-alias signal processing on the second subband signal prior to the synthesis operation of the synthesis filter bank. According to an optional feature of the invention, each subband of the first subband signal comprises a plurality of sub-subbands and the conversion means comprises a second synthesis filter bank for generating the subbands of the second subband signals from sub-subbands of the first subband signal. This may provide an efficient means of converting the first subband signal. The feature may provide for an efficient and/or low complexity means of compensating for a frequency response of the subband filters of the synthesis filter bank. According to an optional feature of the invention, each subband of the second subband signal comprises an alias band and a non-alias band and wherein the conversion means comprises splitting means for splitting a sub-subband of the first subband signal into an alias sub-subband of a first subband band of the second subband signal and a non-alias subband of a second subband of the second subband signal, the alias subband and the non-alias subband having corresponding frequency intervals in the time domain signal. This may provide an efficient means of converting the first subband signal. In particular, it may allow signal components in different subbands originating from the same frequency in the time domain audio signal to be generated from a single signal component. According to an optional feature of the invention, the splitting means comprises a Butterfly structure. This may allow a particularly efficient implementation and/or high performance. The Butterfly structure may use one zero value input and one sub-subband data value input to generate two output values corresponding to different subbands of the second subband. This may provide an efficient means of converting the first subband signal. The feature may provide for an efficient and/or low complexity means of compensating for a frequency response of the subband filters of the first subband. According to an optional feature of the invention, the second filter "bank is oddly stacked. This may improve performance and allow improved separation betrween positive and negative frequencies in the complex subband domain. According to an optional feature of the invention, each subband coxnprises some alias sub-subbands corresponding to an alias band of the subband and some non-alias sub-subbands corresponding to a non-alias band of the subband; and wherein the conversion means comprises combining means for combining alias sub-subbands of a first stx/bband band with non-alias sub-subbands of a second subband, the alias sub-subbands and the non-alias sub-subbands having corresponding frequency intervals in the time domain signal. This may provide an efficient means of converting the first subband signal. In particular, it may allow signal components in different subbands originating from the same frequency in the time domain audio signal to be combined into a single signal component. This may allow a reduction in the data rate. According to an optional feature of the invention, the combining means are arranged to reduce an energy in the alias band. This may improve performance and/or may allow a data rate reduction. In particular, the energy in the alias band may be minimized and the alias bands may be ignored. In particular, the combining means may further comprise means foi compensating non-alias sub-subbands of a first subband band by alias subbands of a second subband. In particular, the combining means may comprise means for subtracting the coefficients of the alias subbands of a second subband from the non-alias sub-sub~bands of a first subband. According to an optional feature of the invention, the combining means comprises means for generating a non-alias sum signal for a first alias sub-subbantd in the first subband and a first non-alias sub-subband in the second subband. This may allow a particularly efficient implementation and/or high performance. According to an optional feature of the invention, the combining means comprises a Butterfly structure for generating the non-alias sum signal. Fig. £ illustrates examples of down-sampled QMF subband filter spectra; Fig. 9 illustrates examples of QMF subband spectra; Fig. 10 illustrates examples of spectra of a subband filter bank; and Fig. 11 illustrates an example of Butterfly transform structures. Fig. 1 illustrates a transmission system 100 for communication of an audio signal in accordance with some embodiments of the invention. The transmission system 100 comprises a transmitter 101 which is coupled to a receiver 103 through a network 105 which specifically may be the Internet. In the specific example, the transmitter 101 is a signal recording device and the receiver is a signal player device 103 but it will be appreciated that in other embodiments a transmitter and receiver may used in other applications and for other purposes. For example, the transmitter 101 and/or the receiver 103 may be part of a transcoding functionality and may e.g. provide interfacing to other signal sources or destinations. In the specific example where a signal recording function is supported, the transmitter 101 comprises a digitizer 107 which receives an analog signal that is converted to a digital PCM signal by sampling and analog-to-digital conversion. The transmitter 101 is coupled to the encoder 109 of Fig. 1 which encodes the PCM signal in accordance with an encoding algorithm. The encoder 100 is coupled to a network transmitter 111 which receives the encoded signal and interfaces to the Internet 105. The network transmitter may transmit the encoded signal to the receiver 103 through the Internet 105. The receiver 103 comprises a network receiver 113 which interfaces to the Internet 105 and which is arranged to receive the encoded signal from the transmitter 101. The network receiver 111 is coupled to a decoder 115. The decoder 115 receives the encoded signal and decodes it in accordance with a decoding algorithm. In the specific example where a signal playing function is supported, the receiver 103 farther comprises a signal player 117 which receives the decoded audio signal from the decoder 115 and presents this to the user. Specifically, the signal player 113 may comprise a digital-to-analog converter, amplifiers and speakers as required for outputting the decoded audio signal. Fig. 2 illustrates the encoder 109 of Fig. 1 in more detail. The encoder 109 comprises a receiver 201 which receives a time domain audio signal to be encoded. The audio signal ma}' be received from any external or internal source, such as from a local signal storage. The receiver is coupled to a first filter bank 203 which generates a subband signal comprising a plurality of different subbands. Specifically, the first filter bank 203 can be a QMF filter bank as known from parametric encoding techniques such as SBR, PS and SAC. Thus, th- first filter bank 203 generates a first subband signal which corresponds to a non-critically sampled complex subband domain representation of the time domain signal. In the specific example, the first subband signal has an oversampling factor of two as is well-known for complex-modulated QMF filters. Since each QMF band is oversampled by a factor of two, it is possible to perform many signal processing operations on the individual subbands without introducing any aliasing distortion. For example, each individual subband may e.g. be scaled and/or other subbands can be added or subtracted etc. Thus, in some embodiments, the encoder 109 further comprises means for performing non-alias signal processing operations on the QMF subbands. The first subband signal corresponds to subband signals conventionally generated by parametric extension encoders such as SBR, PS and SAC. Thus, the first subband signal may be used to generate a parametric extension encoding for the time domain signal. In addition, the same subband signal is in the encoder 109 of Fig. 2 also used for a waveform encoding of the time domain signal Thus, the encoder 109 can use the same filter bank 203 for parametric and waveform encoding of a signal. The main difficulty in waveform coding the complex valued sub-band domain representation of the first subband signal is that it does not form a compact representation, i.e., it is oversL:.apled by a factor of two. The encoder 109 directly transforms the complex sub-band domain representation into a representation that closely resembles a representation which would have been obtained when applying a Modified Discrete Cosine Transform (MDCT) directly to the original time domain signal(See for example H. Malvar, "Signal Processing with Lapped Transforms", Artech House, Boston, London, 1992 for a description of the MDCT). This MDCT-like representation is critically sampled. As such, this signal is suitable for known perceptual audio coding techniques which can be applied in order to efficiently code the resulting representation resulting in an efficient waveform encoding. In particular, the encoder 109 comprises a conversion processor 205 which generates a second subband signal from the first subband signal by applying a complex transform to the individual subbands of the first subband signal. The second subband signal fed to the combiner which combines the two signals to generate a single signal component. This single signaJ component is then encoded by the encode processor 207. Fig. 3 illustrates an example of some elements of the conversion processor 205. In particular, Fig. 3 illustrates a first conversion filter bank 301 for a first QMF subband and a second conversion filter bank 303 for a second QMF subband. The signals from the sub-subbands which correspond to the same frequencies are then fed to the combiner 305 which generates a single output data value for the sub-subband. It will be appreciated that the decoder 115 may perform the inverse operations of the encoder 109. Fig. 4 illustrates the decoder 115 in more detail. The decoder comprises a receiver 401 which receives the signal encoded by the encoder 109 from the network receiver 113. The encoded signal is passed to a decoding processor 403 which decodes the waveform encoding of the encode processor 207 thereby recreating the critically sampled subband signal. This signal is fed to a decode conversion processor 405 which recreates the non-critically sampled subband signal by performing the inverse operation of the conversion processor 205. The non-critically sampled signal is then fed to a QMF synthesis filter 407 which generates a decoded version of the original time domain audio encoding signal. In particular, the decode conversion processor 405 comprises a splitter, such as an inverse Butterfly structure, that regenerates the signal components in the sub-subbands including the signal bands in both the alias and non-alias bands. The sub-subband signals are then fed to a synthesis filter bank corresponding to the conversion filter bank 301, 303 of the encoder 109. The output of these filter banks correspond to the non-critically sampled subband signal. Specific embodiments of the invention will be described in more detail in the following. The description of the embodiments will be described with reference to the encoder structure 500 of Fig. 5. The encoder structure 500 may specifically be implemented in the encoder 109 of Fig. 1. The encoder structure 500 comprises a 64 band analysis QMF filter bank 501. The QMF analysis sub-band filter can be described as follows. Given a real valued linear phase prototype filter p(v), an M-band complex modulated analysis filter bank can be defined by the analysis filters for sub-band index k = 0,1,..., M -1. The phase parameter 0 has importance for the analysis that follows. A typical choice is (N + M)/2 , where N is the prototype filter order. Siven a real valued discrete time signal x(v), the sub-band signals vk (R) are obtained by filtering (convolution) x(v) with hk(y), and then downsampling the result by a factor M as illustrated by the left hand side of Fig. 6 which illustrates the operation of the QMF analysis and synthesis filter banks of the encoder 109 and the decoder 135. Assume that a synthesis operation consists of first upsampling the QMF sub-band signals with a factor M , followed by filtering with complex modulated filters of type similar to equation (1), adding the results and finally taking twice the real part as illustrated by the right hand side of Fig. 6. In such a case, near-perfect reconstruction of the real valued input signal x(v) can be obtained by suitable design of a real valued linear phase prototype filter p(y), as shown in P. Ekstrand, "Bandwidth extension of audio signals by spectral band replication", Proc. 1st IEEE Benelux Workshop on Model based Processing and Coding of Audio (MPCA-2002), pp. 53-58, Leuven, Belgium, November 15 2002. In the following, let be the discrete time Fourier transform of a discrete time signal z(n). In addition lo the near-perfect reconstruction property of the QMF bank, it will be assumed that P(co), the Fourier transform of p(v) , essentially vanishes outside the frequency interval [—K i M, n i M]. The Fourier transform of the downsampled complex sub-band domain signals is given by: where k is the sub-band index and M is the number of subbands. Due to the assumption of the frequency response of the prototype filter being limited, the sum in equation (2) contains only one term each co. The corresponding stylized absolute frequency responses are shown in Fig. 7 and Fig. 8. Specifically, Fig. 7 illustrates the stylized frequency responses for the first few frequency bands of the complex QMF bank 501 prior to downsampling. Fig. 8 illustrates the stylized frequency responses of the downsampled complex QMF bank for even (top) and odd (bottom) subbands k. Thus, as illustrated in Fig. 8 the center of a QMF filter band will after down sampling be aliazed to nil for even numbered subbands and to -7t/2 for uneven numbered subbands. Fi7. 8 illustrates the effect of the oversampling of the complex QMF bank. For the bands with even index k and odd index k, respectively the negative and positive part of the frequency spectrum are not required in order to reconstruct the (originally real-valued) signal. These parts of the frequency spectrum of the downsampled filter bank will be referred to as the aliazed bands or stop bands, whereas the other parts will be indicated as the pass band or non-aliazed band. It is noted that the aliazed bands contain information which is also present in the pass bands of the spectra of other subbands. This particular property will be used to derive an efficient coding mechanism. It will be appreciated that the alias and non-alias bands comprises redundant information and "hat one can be determined from the other. It will also be appreciated that the complementary interpretation of alias and non-alias bands can be used. As will be shown in the following, the energies corresponding to the aliazed bands (or stop bands) of the QMF analysis filter bank can be reduced to zero or negligible values by applying a certain type of additional filter bank 503 at each output of the down-sampled analysis filter bank 501 and applying certain butterfly structures 505 between the outputs of the additional filter banks 501. As a consequence, half of the information, i.e., half of the filter bank outputs can be discarded. As a result, a critically sampled representation is obtained. This representation is . ery similar to the representation achieved by an MDCT transform of the original time domain samples and therefore closely resembles the subband signals which are generated by typical waveform encoders such as MP3 or AAC. Accordingly, waveform encoding techniques can be applied directly to the critically sampled signal in the waveform encode processor 507 and no requirement for a conversion to the time domain followed by an MDCT subband generation is required. The resulting encoded data is then included in a bitstream by a bitstream processor 509. Fig. 9 illustrates the effect of the QMF subband generation for a signal consisting of two sinusoids. In the complex, frequency domain (such as e.g. obtained by means of an FF1~3 each sinusoid will show up in the spectrum as both a positive and negative frequency. Now assume a 8-bands complex QMF bank (in the example of Fig. 5 a 64-bands bank is employed). Prior to downsampling, the sinusoids will show up as illustrated in spectra A to H. As illustrated, each sinusoid occurs in two subbands, e.g. the low frequency spectral line occurs in both spectrum A, corresponding to the first QMF subband, as well as spectrum B, corresponding to the second QMF subband. The process of downsampling of the QMF bank is illustrated in the lower pajrt of Fig. 9, where spectrum I shows the spectrum prior to downsampling. The downsampling procedure can be interpreted as following. First the spectrum is split into M spectra A to H, where M is the downsampling factor (M-8) as illustrated in I and K for the first and second-sub-band respectively. Each individual split spectrum is expanded (stretched) again to the full frequency range. Then all the individual split and expanded spectra are added resulting in thae spectra as illustrated in spectrum J and L for the first and second sub-band respectively. In summary, due to the filter of each individual subband having a bandwidth which exceeds the frequency interval between subbands, signal components of the time domain signal will result in signal components in two different subbands. Furthermore, one of these signal components will fall in the alias band of one of the subbands and one will fall in the non-alias band of the other subband. Thus, as shown in spectrum J and L7 in the final output spectra of the complEix QMF bank, the components still occur in two sub-bands, e.g., the low frequency spectral lime occurs in the pass band of the first subband as well as in the stop-band of the second subbamd. The magnitude of the spectral line in both cases is given by the frequency response of the (shifted) prototype filter. In .accordance with the embodiments of Fig. 5, an additional set of complex transforms (the filter bank 503) is introduced where each transform is applied to the output of a sub-band. This is used to further split the frequency spectrum of those sub-bands into a plurality of sub-subbands. Each sub-subband in the pass band of a QMF subband is then combined with_ the correspond sub-subband of the alias band in the adjacent QMF subband. In the example., the sub-subband comprising the low frequency sinusoid in spectrum J is combined with the low frequency sinusoid in spectrum L thus resulting in both signal components arising from.. the same low frequency sinusoid of the time domain signal being combined into a single signal componer-. Furthermore, in order to compensate for the frequency response of the QMF prototype filter, the value from each sub-subband is weighted by the relative amplitude of the frequency response before the combining (it is assumed that the amplitude response of the QMF prototype filter is constant within each sub-subband). The signal components in the stop bands can be ignored or may be compensated by the values from the pass band thereby effectively reducing the energy in the alias band. Thus, the operation of the conversion processor 207 can be seen as corresponding to concentrating the energy of the two signal components arising for each frequency into a single signal component in the pass band of one of the QMF subbands. Thus, as the sigpnal values in the alias or stop bands can be ignored, an efficient down sampling by two can be achieved resulting in a critically sampled signal. As will be shown in the following, the combining of the signal components (and the cancellation of signal components in the alias bands) can be achieved by using a Butterfly structure. In principle, applying another (50% overlapping) complex transform (by the filter banks 503) on the sub-band signals would yield another upsampling of a factor of 2. However, the chosen transforms possess a certain symmetric property allowing a reduction of 50% of the data. The resulting transform can be considered equivalent to applying an MDCT to the real data and an MDST to the imaginary data. Both are critically sampled transforms, and thus no, upsampling occurs. In, more detail, the filter banks 503 can be a complex-modulated filter ba.nk consisting of R = 2Q bands. An example of a stylized frequency response of the filter "banks 503 for each subband are shown in Fig. 10, for each sub-band k. As can be seen the fiLter bank is oddly stacked and has no subband centered around the DC value. Rather, in the example, the center frequencies of the subbands are symmetric around zero with the center frequency of the fust subband being around half the subband frequency offset. The downsampling factor in this second bank is O and it is defined by the where the real valued prototype window w(y) is such that w(y) = w(—v -1 - O). It is well known thai this window can be designed such that perfect reconstruction can be achieved from analysis in a filter bank with filters being equal to either the real part of (3) or the imaginary part of (3). In those cases, only Q of the R~2Q subbands suffice, either positive or negative frequencies. A prominent example is the modified discrete cosine transform MDCT. However, in the embodiment of Fig. 5 a complex valued signal z{n) is instead analyzed with the filters 503, the resulting signals are downsampled by a factor (2 and the real part is taken. The corresponding synthesis operation consists of upsampling by a factor 0, and synthesis filtering by the complex modulated filters, summing the results over the R = 20 subbands, r = -~Q, -Q +1,..., Q -1, and finally dividing the result by two. If the prototype window w(v) is designed to give perfect reconstruction in the real valued banks mentioned above, the combined operation of analysis and synthesis in the complex case will perfectly reconstruct the complex valued signal z(n). To see this, let C represent the analysis bank that has analysis filters equal to the real part of (3), and let S represent the analysis bank that has analysis filters equal to minus the imaginary part of (3). Then the complex analysis bank (3) can be written as E = C-iS. Writing the complex signal Here (5) is evaluated for both positive frequencies r ~ 0,..., Q -1, and negative frequencies r --Q,...,-\. Note that changing rto -1 -rin (3) leads to a complex conjugation of tAe analysis filter, so the analysis (5) gives access to both Ct; + S77 and Cc - Srj for positive frequencies r - 0,..., O -1. For synthesis this information can be easily recornbined into Ct; and Sr\, from which perfect reconstruction of both t and 7] is possible with the corresponding real valued synthesis banks. We omit the straightforward details of proving the claim that this reconstruction is equivalent to the operation of complex analysis, real part, complex synthesis, and division by two. This filter bank structure is related, but not identical to, the modified DFT (MDFT) filter banks as proposed in Karp T., Fliege NJ., 'Modified DFT Filter Banks with Perfect Reconstruction", IEEE Transactions on Circuits and Systems-II: Analog and Digital Signal Processing, Vol. 46, No. 13, November 1999. A principal difference is that the present iilter bank is oddly stacked, a fact which is advantageous for the following proposed hybrid structure. For each fc = 0,l9...,Af-l and r = -2,-2 + 1,...yQ-1, let vkr(n) be the sub- subband signal achieved by analysis of the complex QMF analysis signal yk(y) with the analysis filter 503, downsampling by a factor Q, and taking the real part. This gives a total of 2QM real valued signals at a sampling rate of 1 l{QM) of the original sampling rate. Hence, a representation oversampled by a factor two is obtained. Referring to Figs. 8 and 10, it is convenient to define the pass band signals by where C is a complex constant. As a result, neighboring QMF bands will thus contain complex sinusoids with the same frequency and phase but with different magnitudes, due the response of the modulated linear phase QMF prototype filter. Thus, as mentioned previously, TWO signal components arise - one in the pass band of one QMF subband and one in the alias band of an adjacent subband. Transforming the corresponding pairs of sub-subband samples into weighted sums and differences will therefore lead to very small differences. Before the details of this transform is outlined, it should be pointed out that if the assumption that 8 = 0 is not satisfied, the QMF samples should preferably be phase compensated by being pre-multiplied (pre-twiddling) in a pre-twiddle processor 511 according to Fig. 11 illustrates the corresponding transform Butterfly structures. These butterfly structures are similar to those used in MPEG-1 Layer III (MP3). However, an important difference is that the so-called anti-aliasing butterflies of mp3 are used to reduce the aliasing in the pass bands of the real-valued filter bank. In a real modulated filter bank, it is not possible to distinguish between positive and negative (complex) frequencies in the subbands. In the synthesis step, one sinusoid in the subband will therefore generally give rise to-two sinusoids in the output. One of those, the aliazed sinusoid, is located at a frequency quilt far from the correct frequency. The real bank anti-aliasing butterflies aim at suppressing the aliazed sinusoid by directing the second hybrid bank synthesis into two neighboring real QMF bands. The present approach differs fundamentally from this situation in that the complex QMF subband is fed with a complex sinusoid from the second hybrid bank. This gives rise to only one correctly located sinusoid in the final output, and the alias problem of MPS never occurs. The Butterfly structures 505 aim solely at correcting the magnitude response of the combined analysis and synthesis operation, when the difference signals d are omitted. Note first that if the transform coefficients are set to /3kr = l and ak f - 0, then the signal pair (s, d) will just be a copy of the pair (6, a). This can be done in a selective way since the structure of (10) and (11) is such that computations can be done in place. This has importance for the case where the hybrid filter bank structure is only invoked for a subset of QMF bands. All the sum and difference operations are invertible as long as f5kr +tf;2r > 0 and the transformation is orthogonal if fikr+ockr = 1. The corresponding synthesis steps are very similar to (10) and (11) and will be clear to the skilled person. This holds also for the inversion of the pre-twiddling by the pre- twiddle processor 511. The present approach teaches that the signals dk r (n) become very small for the choice where So, under the assumption that the additional filter bank for each sub-band k is critically sampled and perfectly reconstructing, the approximation of the alias band sub-subband domain signals practically reduces the oversampled representation to a critically sampled representation closely resembling the MDCT of the original time domain samples. This allows efficient coding of the complex sub-band domain signals in a fashion similar to known perceptual waveform coders. The reconstruction error of discarding the transform coefficients corresponding to the stop or alias bands is in the order of 34 dB for a typical transform length Q=16. Alternatively the coefficients corresponding to the stop bands or alias bands could be encoded additionally to the coefficients corresponding to the pass bands in order to obtain a better reconstruction. This could be beneficial in case Q is very small (e.g. Q Tn the example of Fig. 5, the sum-difference butterflies of (10) and (11) 505 are applied in order to obtain the signal pair (s, d) of which in this case only the dominant components (s) are preserved. In a next step, conventional waveform coding techniques using e.g. scale-factor coding and quantization are applied on the resulting signal(s). The coded coefficients are embedded into a bit stream. The decoder follows the inverse process. First, the coefficients are demultiplexed from the bit stream and decoded. Then, the inverse butterfly operation of the encoder is applied followed by synthesis filtering and post-twiddling to obtain the complex sub-band domain signals. These can finally be transformed to the time domain by means of the QMF synthesis bank. It will be appreciated that the above description for clarity has described embodiments of the invention with reference to different functional units and processors. However, it will be apparent that any suitable distribution of functionality between different functional units or processors may be used without detracting from the invention. For example, functionality illustrated to be performed by separate processors or controllers may be performed bv the same processor or controllers. Hence, references to specific functional units are only to be seen as references to suitable means for providing the described functionality rather than indicative of a strict logical or physical structure or organization. The invention can be implemented in any suitable form including hardware, software, firmware or any combination of these. The invention may optionally be implemented at least partly as computer software running on one or more data processors and/or digital signal processors. The elements and components of an embodiment of the invention may be physically, functionally and logically implemented in any suitable way. Indeed the functionality may be implemented in a single unit, in a plurality of units or as part of other functional units. As such, the invention may be implemented in a single unit or may be physically and functionally distributed between different units and processors. Although the present invention has been described in connection with some embodiments, it is not intended to be limited to the specific form set forth herein. Rather, the scope of the pr sent invention is limited only by the accompanying claims. Additionally, although a feature may appear to be described in connection with particular embodiments, one skilled in the art would recognize that various features of the described embodiments may be combined in accordance with the invention. In the claims, the term comprising does not exclude the presence of other elements or steps. Furthermore, although individually listed, a plurality of means, elements or method steps may be implemented by e.g. a single unit or processor. Additionally, although individual features may be included in different claims, these may possibly be advantageously combined, and the inclusion in different claims does not imply that a combination of features is not feasible and/or advantageous. Also the inclusion of a feature in one category of claims does not imply a limitation to this category but rather indicates that the feature is equally applicable to other claim categories as appropriate. Furthermore, the order of features in the claims do not imply any specific order in which the features must be worked and in particular the order of individual steps in a method claim does not imply that the steps must be performed in this order. Rather, the steps may be performed in any suitable order, hi addition, singular references do not exclude a plurality. Thus references to "a", "an", "first", "second" etc do not preclude a plurality. Reference signs in the claims are provided merely as a clarifying example shall not be construed as limiting the scope of the claims in any way. CLAIM. A decoder for generaung a lime domain audio signal by waveform decoding, die decoder comprising: means for receiving (401) an encoded data stream;

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1868-CHENP-2007 FORM-3 19-08-2014.pdf

1868-CHENP-2007 OTHER PATENT DOCUMENT 19-08-2014.pdf

1868-CHENP-2007 OTHERS 19-08-2014.pdf

1868-CHENP-2007 POWER OF ATTORNEY 19-08-2014.pdf

1868-chenp-2007-abstract.pdf

1868-chenp-2007-claims.pdf

1868-chenp-2007-correspondnece-others.pdf

1868-chenp-2007-description(complete).pdf

1868-chenp-2007-drawings.pdf

1868-chenp-2007-form 1.pdf

1868-CHENP-2007-Form 13.pdf

1868-chenp-2007-form 3.pdf

1868-chenp-2007-form 5.pdf

1868-chenp-2007-pct.pdf

1868-CHENP-2007-Petition for Annexure.pdf

1868CHENP2007-Petition for POR.pdf