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S. Barbarossa - One of the best experts on this subject based on the ideXlab platform.
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Filterbank transceivers optimizing information rate in block transmissions over dispersive channels
IEEE Transactions on Information Theory, 1999Co-Authors: Anna Scaglione, S. Barbarossa, Georgios B GiannakisAbstract:Optimal finite impulse response (FIR) transmit and receive Filterbanks are derived for block-based data transmissions over frequency-selective additive Gaussian noise (AGN) channels by maximizing mutual information subject to a fixed transmit-power constraint. Both FIR and pole-zero channels are considered. The inherent flexibility of the proposed transceivers is exploited to derive, as special cases, zero-forcing (ZF) and minimum mean-square error receive Filterbanks. The transmit Filterbank converts transmission over a frequency-selective fading channel, affected by additive colored noise, into a set of independent flat fading subchannels with uncorrelated noise samples. Two loading algorithms are also developed to distribute transmit power and number of bits across the usable subchannels, while adhering to an upper bound on the bit error rate (BER). Reduction of the signal-to-noise ratio (SNR) margin required to satisfy the prescribed BER is achieved by coding each subchannel's bit stream. The potential of the proposed transceivers is illustrated and compared to discrete multitone (DMT) with simulated examples.
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Redundant Filterbank precoders and equalizers. I. Unification and optimal designs
IEEE Transactions on Signal Processing, 1999Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:Transmitter redundancy introduced using Filterbank precoders generalizes existing modulations including OFDM, DMT, TDMA, and CDMA schemes encountered with single- and multiuser communications. Sufficient conditions are derived to guarantee that with FIR Filterbank precoders FIR channels are equalized perfectly in the absence of noise by FIR zero-forcing equalizer Filterbanks, irrespective of the channel zero locations. Multicarrier transmissions through frequency-selective channels can thus be recovered even when deep fades are present. Jointly optimal transmitter-receiver Filterbank designs are also developed, based on maximum output SNR and minimum mean-square error criteria under zero-forcing and fixed transmitted power constraints. Analytical performance results are presented for the zero-forcing Filterbanks and are compared with mean-square error and ideal designs using simulations.
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Redundant Filterbank precoders and equalizers. II. Blind channel estimation, synchronization, and direct equalization
IEEE Transactions on Signal Processing, 1999Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:For pt.I see ibid., vol.47, no.7, p.1988-2006 (1999). Transmitter redundancy introduced using finite impulse response (FIR) Filterbank precoders offers a unifying framework for single- and multiuser transmissions. With minimal rate reduction, FIR Filterbank transmitters with trailing zeros allow for perfect (in the absence of noise) equalization of FIR channels with FIR zero-forcing equalizer Filterbanks, irrespective of the input color and the channel zero locations. Exploiting this simple form of redundancy, blind channel estimators, block synchronizers, and direct self-recovering equalizing Filterbanks are derived in this paper. The resulting algorithms are computationally simple, require small data sizes, can be implemented online, and remain consistent (after appropriate modifications), even at low SNR colored noise. Simulations illustrate applications to blind equalization of downlink CDMA transmissions, multicarrier modulations through channels with deep fades, and superior performance relative to CMA and existing output diversity techniques relying on multiple antennas and fractional sampling.
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Redundant Filterbank precoders and equalizers: unification and optimal designs
ICC '98. 1998 IEEE International Conference on Communications. Conference Record. Affiliated with SUPERCOMM'98 (Cat. No.98CH36220), 1998Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:Transmitter redundancy introduced using Filterbank precoders generalizes existing modulations including OFDM, DMT, TDMA, and CDMA schemes encountered with single- and multi-user communications. Sufficient conditions are derived to guarantee that, with FIR Filterbank preceders, FIR channels are equalized perfectly in the absence of noise by FIR zero-forcing equalizer Filterbanks, irrespective of the channel zero locations. Multicarrier transmissions through frequency-selective channels can thus be recovered even when deep fades are present. Jointly optimal transmitter-receiver Filterbank designs are also developed based on maximum output SNR and minimum mean-square error criteria under zero-forcing and fixed transmitted power constraints. Analytical performance results are presented for the zero-forcing Filterbanks and are compared with mean-square error and ideal designs using simulations.
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Self-recovering multirate equalizers using redundant Filterbank precoders
Proceedings of the 1998 IEEE International Conference on Acoustics Speech and Signal Processing ICASSP '98 (Cat. No.98CH36181), 1998Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:Transmitter redundancy introduced using FIR Filterbank precoders offers a unifying framework for single- and multi-user transmissions. With minimal rate reduction, FIR Filterbank transmitters with trailing zeros allow for perfect (in the absence of noise) equalization of FIR channels with FIR zero-forcing equalizer Filterbanks, irrespective of the input color and the channel zero locations. Methods of exploiting input diversity, blind channel estimators, block synchronizers, and direct self-recovering equalizing Filterbanks are derived. The resulting algorithms are computationally simple, require small data sizes, can be implemented online, and remain consistent (after appropriate modifications) even at low SNR colored noise. Simulations illustrate applications to multi-carrier modulation through channels with deep fades, and superior performance relative to the constant modulus algorithm (CMA) and existing output diversity techniques relying on multiple antennas and fractional sampling.
A. Scaglione - One of the best experts on this subject based on the ideXlab platform.
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Self-recovering transceivers for block transmissions: Filterbank precoders and decision-feedback equalizers
1999 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications (Cat. No.99EX304), 1999Co-Authors: A Stamoulis, G.b. Giannakis, A. ScaglioneAbstract:Transmitter induced redundancy using FIR Filterbanks can be used to equalize FIR channels irrespective of channel zeros and facilitate blind channel estimation. At the receiver end, linear or non-linear (DFE) FIR Filterbanks can be applied to recover the transmitted data. Closed form expressions are derived for the FIR linear or DFE Filterbank receivers. By applying blind channel estimation methods, the resulting DFE-framework becomes self-recovering. Extensive simulations illustrate the merits of our designs.
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Redundant Filterbank precoders and equalizers. I. Unification and optimal designs
IEEE Transactions on Signal Processing, 1999Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:Transmitter redundancy introduced using Filterbank precoders generalizes existing modulations including OFDM, DMT, TDMA, and CDMA schemes encountered with single- and multiuser communications. Sufficient conditions are derived to guarantee that with FIR Filterbank precoders FIR channels are equalized perfectly in the absence of noise by FIR zero-forcing equalizer Filterbanks, irrespective of the channel zero locations. Multicarrier transmissions through frequency-selective channels can thus be recovered even when deep fades are present. Jointly optimal transmitter-receiver Filterbank designs are also developed, based on maximum output SNR and minimum mean-square error criteria under zero-forcing and fixed transmitted power constraints. Analytical performance results are presented for the zero-forcing Filterbanks and are compared with mean-square error and ideal designs using simulations.
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Redundant Filterbank precoders and equalizers. II. Blind channel estimation, synchronization, and direct equalization
IEEE Transactions on Signal Processing, 1999Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:For pt.I see ibid., vol.47, no.7, p.1988-2006 (1999). Transmitter redundancy introduced using finite impulse response (FIR) Filterbank precoders offers a unifying framework for single- and multiuser transmissions. With minimal rate reduction, FIR Filterbank transmitters with trailing zeros allow for perfect (in the absence of noise) equalization of FIR channels with FIR zero-forcing equalizer Filterbanks, irrespective of the input color and the channel zero locations. Exploiting this simple form of redundancy, blind channel estimators, block synchronizers, and direct self-recovering equalizing Filterbanks are derived in this paper. The resulting algorithms are computationally simple, require small data sizes, can be implemented online, and remain consistent (after appropriate modifications), even at low SNR colored noise. Simulations illustrate applications to blind equalization of downlink CDMA transmissions, multicarrier modulations through channels with deep fades, and superior performance relative to CMA and existing output diversity techniques relying on multiple antennas and fractional sampling.
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Redundant Filterbank precoders and equalizers: unification and optimal designs
ICC '98. 1998 IEEE International Conference on Communications. Conference Record. Affiliated with SUPERCOMM'98 (Cat. No.98CH36220), 1998Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:Transmitter redundancy introduced using Filterbank precoders generalizes existing modulations including OFDM, DMT, TDMA, and CDMA schemes encountered with single- and multi-user communications. Sufficient conditions are derived to guarantee that, with FIR Filterbank preceders, FIR channels are equalized perfectly in the absence of noise by FIR zero-forcing equalizer Filterbanks, irrespective of the channel zero locations. Multicarrier transmissions through frequency-selective channels can thus be recovered even when deep fades are present. Jointly optimal transmitter-receiver Filterbank designs are also developed based on maximum output SNR and minimum mean-square error criteria under zero-forcing and fixed transmitted power constraints. Analytical performance results are presented for the zero-forcing Filterbanks and are compared with mean-square error and ideal designs using simulations.
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Self-recovering multirate equalizers using redundant Filterbank precoders
Proceedings of the 1998 IEEE International Conference on Acoustics Speech and Signal Processing ICASSP '98 (Cat. No.98CH36181), 1998Co-Authors: A. Scaglione, G.b. Giannakis, S. BarbarossaAbstract:Transmitter redundancy introduced using FIR Filterbank precoders offers a unifying framework for single- and multi-user transmissions. With minimal rate reduction, FIR Filterbank transmitters with trailing zeros allow for perfect (in the absence of noise) equalization of FIR channels with FIR zero-forcing equalizer Filterbanks, irrespective of the input color and the channel zero locations. Methods of exploiting input diversity, blind channel estimators, block synchronizers, and direct self-recovering equalizing Filterbanks are derived. The resulting algorithms are computationally simple, require small data sizes, can be implemented online, and remain consistent (after appropriate modifications) even at low SNR colored noise. Simulations illustrate applications to multi-carrier modulation through channels with deep fades, and superior performance relative to the constant modulus algorithm (CMA) and existing output diversity techniques relying on multiple antennas and fractional sampling.
Hemant A Patil - One of the best experts on this subject based on the ideXlab platform.
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novel unsupervised auditory Filterbank learning using convolutional rbm for speech recognition
IEEE Transactions on Audio Speech and Language Processing, 2016Co-Authors: Hardik B Sailor, Hemant A PatilAbstract:To learn auditory Filterbanks, recently, we have proposed an unsupervised learning model based on convolutional restricted Boltzmann machine RBM with rectified linear units. In this paper, theory, training algorithm of our proposed model, and detailed analysis of learned Filterbank are being presented. Learning of the model with different databases shows that the model is able to learn cochlear-like impulse responses that are localized in frequency-domain. An auditory-like scale obtained from Filterbanks learned from clean and noisy datasets resembles the Mel scale, which is known to mimic perceptually relevant aspect of speech. We have experimented with both cepstral denoted as ConvRBM-CC as well as Filterbank features denoted as ConvRBM-BANK. On large vocabulary continuous speech recognition task, we achieved relative improvement of 7.21-17.8% in word error rate WER compared to Mel frequency cepstral coefficient MFCC features and 1.35-6.82% compared to Mel Filterbank FBANK features. On AURORA 4 multicondition training database, the relative improvement in WER by 4.8-13.65% was achieved using a Hybrid Deep Neural Network-Hidden Markov Model DNN-HMM system with ConvRBM-CC features. Using ConvRBM-BANK features, we achieve absolute reduction of 1.25-3.85% in WER on AURORA 4 test sets compared to FBANK features. A context-dependent DNN-HMM system further improves performance with a relative improvement of 3.6-4.6% on an average for bigram 5k and tri-gram 5k language models. Hence, our proposed learned Filterbank performs better than traditional MFCC and Mel-Filterbank features for both clean and multicondition automatic speech recognition ASR tasks. A system combination of ConvRBM-BANK and FBANK features further improve performance in all ASR tasks. Cross-domain experiments where subband filters trained on one database are used for the ASR task of another database show that model learns generalized representations of speech signals.
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Filterbank learning using convolutional restricted boltzmann machine for speech recognition
International Conference on Acoustics Speech and Signal Processing, 2016Co-Authors: Hardik B Sailor, Hemant A PatilAbstract:Convolutional Restricted Boltzmann Machine (ConvRBM) as a model for speech signal is presented in this paper. We have developed ConvRBM with sampling from noisy rectified linear units (NReLUs). ConvRBM is trained in an unsupervised way to model speech signal of arbitrary lengths. Weights of the model can represent an auditory-like Filterbank. Our proposed learned Filterbank is also nonlinear with respect to center frequencies of subband filters similar to standard Filterbanks (such as Mel, Bark, ERB, etc.). We have used our proposed model as a front-end to learn features and applied to speech recognition task. Performance of ConvRBM features is improved compared to MFCC with relative improvement of 5% on TIMIT test set and 7% on WSJ0 database for both Nov'92 test sets using GMM-HMM systems. With DNN-HMM systems, we achieved relative improvement of 3% on TIMIT test set over MFCC and Mel Filterbank (FBANK). On WSJ0 Nov'92 test sets, we achieved relative improvement of 4–14% using ConvRBM features over MFCC features and 3.6–5.6% using ConvRBM Filterbank over FBANK features.
Toshio Irino - One of the best experts on this subject based on the ideXlab platform.
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a dynamic compressive gammachirp auditory Filterbank
IEEE Transactions on Audio Speech and Language Processing, 2006Co-Authors: Toshio Irino, Roy D PattersonAbstract:It is now common to use knowledge about human auditory processing in the development of audio signal processors. Until recently, however, such systems were limited by their linearity. The auditory filter system is known to be level-dependent as evidenced by psychophysical data on masking, compression, and two-tone suppression. However, there were no analysis/synthesis schemes with nonlinear Filterbanks. This paper describe 18300060s such a scheme based on the compressive gammachirp (cGC) auditory filter. It was developed to extend the gammatone filter concept to accommodate the changes in psychophysical filter shape that are observed to occur with changes in stimulus level in simultaneous, tone-in-noise masking. In models of simultaneous noise masking, the temporal dynamics of the filtering can be ignored. Analysis/synthesis systems, however, are intended for use with speech sounds where the glottal cycle can be long with respect to auditory time constants, and so they require specification of the temporal dynamics of auditory filter. In this paper, we describe a fast-acting level control circuit for the cGC filter and show how psychophysical data involving two-tone suppression and compression can be used to estimate the parameter values for this dynamic version of the cGC filter (referred to as the "dcGC" filter). One important advantage of analysis/synthesis systems with a dcGC Filterbank is that they can inherit previously refined signal processing algorithms developed with conventional short-time Fourier transforms (STFTs) and linear Filterbanks
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An analysis/synthesis auditory Filterbank based on an IIR implementation of the gammachirp
Journal of the Acoustical Society of Japan (E), 1999Co-Authors: Toshio Irino, Masashi UnokiAbstract:This paper proposes a new auditory Filterbank that enables signal resynthesis from dynamic representations produced by a level-dependent auditory Filterbank. The Filterbank is based on a new IIR implementation of the gammachirp, which has been shown to be an excellent candidate for asymmetric, level-dependent auditory filters. Initially, the gammachirp filter is shown to be decomposed into a combination of a gammatone filter and an asymmetric function. The asymmetric function is excellently simulated with a minimum-phase IIR filter, named the “asymmetric compensation filter”. Then, two Filterbank structures are presented each based on the combination of a gammatone Filterbank and a bank of asymmetric compensation filters controlled by a signal level estimation mechanism. The inverse filter of the asymmetric compensation filter is always stable because the minimum-phase condition is satisfied. When a bank of inverse filters is utilized after the gammachirp analysis Filterbank and the idea of wavelet transform is applied, it is possible to resynthesize signals with small time-invariant errors and achieve a guaranteed precision. This feature has never been accomplished by conventional active auditory Filterbanks. The proposed analysis/synthesis gammachirp Filterbank is expected to be useful in various applications where human auditory filtering has to be modeled.
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an analysis synthesis auditory Filterbank based on an iir implementation of the gammachirp
The Journal of The Acoustical Society of Japan (e), 1999Co-Authors: Toshio Irino, Masashi UnokiAbstract:This paper proposes a new auditory Filterbank that enables signal resynthesis from dynamic representations produced by a level-dependent auditory Filterbank. The Filterbank is based on a new IIR implementation of the gammachirp, which has been shown to be an excellent candidate for asymmetric, level-dependent auditory filters. Initially, the gammachirp filter is shown to be decomposed into a combination of a gammatone filter and an asymmetric function. The asymmetric function is excellently simulated with a minimum-phase IIR filter, named the “asymmetric compensation filter”. Then, two Filterbank structures are presented each based on the combination of a gammatone Filterbank and a bank of asymmetric compensation filters controlled by a signal level estimation mechanism. The inverse filter of the asymmetric compensation filter is always stable because the minimum-phase condition is satisfied. When a bank of inverse filters is utilized after the gammachirp analysis Filterbank and the idea of wavelet transform is applied, it is possible to resynthesize signals with small time-invariant errors and achieve a guaranteed precision. This feature has never been accomplished by conventional active auditory Filterbanks. The proposed analysis/synthesis gammachirp Filterbank is expected to be useful in various applications where human auditory filtering has to be modeled.
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ICASSP - A time-varying, analysis/synthesis auditory Filterbank using the gammachirp
Proceedings of the 1998 IEEE International Conference on Acoustics Speech and Signal Processing ICASSP '98 (Cat. No.98CH36181), 1Co-Authors: Toshio Irino, Masashi UnokiAbstract:A time-varying, analysis/synthesis auditory Filterbank has been developed using a new implementation of the "gammachirp", which has been shown to be an excellent function for the asymmetric, level-dependent auditory filter. The gammachirp filter is shown to be implemented through a combination of a gammatone filter and an IIR asymmetric compensation filter; which largely reduces the computational cost for time-varying filtering. The gammachirp Filterbank is designed using a linear gammatone Filterbank and a bank of time-varying asymmetric compensation filters controlled by the sound pressure level estimated at the output of the Filterbank. Since the inverse filter of the asymmetric compensation filter is always stable, it is possible to resynthesize signals from time-varying, level-dependent auditory representations. The resynthesis error is only determined by the linear analysis/synthesis gammatone Filterbank. The proposed Filterbank is applicable to various types of signal processing required to model human auditory filtering.
H. De Man - One of the best experts on this subject based on the ideXlab platform.
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Critically Subsampled Filterbanks for SISO Reed–Solomon Decoding
IEEE Transactions on Signal Processing, 2006Co-Authors: G. Van Meerbergen, Marc Moonen, H. De ManAbstract:In the last decade, there has been a growing interest in soft decoding techniques. These techniques are used in the context of concatenated codes, with Turbo codes as the main example, but are almost never applied to existing classical codes. In this paper, the family of Reed-Solomon (RS) codes is considered, and the complexity problem of soft-in soft-out (SISO) RS decoding is tackled by breaking RS codes into several smaller subcodes. Finally, the decoders of these subcodes work together in a Turbo-like fashion (Gallager's algorithm) to find an approximate maximum a posteriori (MAP) solution. The decomposition that is presented here is based on critically subsampled Filterbanks, with one subcode in each subband. A critically subsampled Filterbank allows us to define a number of parallel independent subcodes. Furthermore, noncritically subsampled Filterbanks have a larger number of subband variables than the codeword length, causing a message passing decoder (Gallager's algorithm) to fail. This paper focuses on the construction of such Filterbanks, starting from noncritically subsampled Filterbanks, it gradually evolves towards a critically subsampled Filterbank
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ICASSP (2) - Critically subsampled Filterbanks implementing Reed-Solomon codes
2004 IEEE International Conference on Acoustics Speech and Signal Processing, 1Co-Authors: G. Van Meerbergen, Marc Moonen, H. De ManAbstract:The last decade has shown a growing interest in soft decoding techniques. These techniques are almost never applied to existing nearly perfect codes, but instead other families of concatenated codes arise with Turbo codes as the main example. The problem is that for the application of soft decoding, the perfect codes need to be broken into several smaller component codes. In this paper, the family of Reed-Solomon codes is considered, and, using Filterbanks, they are broken into several component codes (one in each subband). This paper focuses on the construction of such Filterbanks, and gradually evolves towards a critically subsampled Filterbank. The critical subsampling is crucial if the Filterbank is going to be used in a soft decoding setup.
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ICC - IIR critically subsampled Filterbanks implementing systematic Reed-Solomon codes
IEEE International Conference on Communications 2005. ICC 2005. 2005, 1Co-Authors: G. Van Meerbergen, Marc Moonen, H. De ManAbstract:The last decade shows a growing interest in soft decoding techniques, motivated by a soft decoding gain of roughly 2dB. Most of the techniques are applied to concatenated codes, with turbo codes as the most famous example. This is in strong contrast with many existing coding schemes where Reed-Solomon (RS) codes are common. Recently, we unveiled an (FIR) Filterbank structure behind the RS codes. Using this Filterbank decomposition, a RS code is broken into many smaller subcodes that can consequently be used to build a SISO RS decoder. The aim of this paper is twofold: in the first part, an algebraic shortcut to construct the FIR Filterbank is presented. This method gives a lot of insight into the algebraic structure of RS codes and their corresponding Filterbanks. In the second part, motivated by the importance of systematic RS codes, a critically subsampled IIR Filterbank structure implementing a systematic RS code is examined. The SISO RS decoder based on the IIR Filterbank shows a lower computational complexity and better performance compared to the FIR counterpart.