A Recursive Method for the Approximation of LTI Systems Using Subband Processing

Marelli, Damián; Fu, Minyue

doi:10.1109/tsp.2009.2034933

Cited by 5 publications

(2 citation statements)

References 29 publications

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“…A drawback of ( 13) is that the obtained has a large number of nonzero entries. In [47], this issue is addressed by using sparse approximation techniques to solve (14) where (15) and is the polyphase representation of a user-supplied spectral weighting function . We summarize this result below, for a more detailed presentation see [47].…”

Section: B Subband Model Designmentioning

confidence: 99%

Time–Frequency Synthesis of Noisy Sounds With Narrow Spectral Components

Marelli

Aramaki

Kronland‐Martinet

et al. 2010

IEEE Trans. Audio Speech Lang. Process.

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The inverse fast Fourier transform (FFT) method was proposed to alleviate the computational complexity of the additive sound synthesis method in real-time applications, and consists in synthesizing overlapping blocks of samples in the frequency domain. However, its application is limited by its inherent tradeoff between time and frequency resolution. In this paper, we propose an alternative to the inverse FFT method for synthesizing colored noise. The proposed approach uses subband signal processing to generate time-frequency noise with an autocorrelation function such that the noise obtained after converting it to time domain has the desired power spectral density. We show that the inverse FFT method can be interpreted as a particular case of the proposed method, and therefore, the latter offers some extra design flexibility. Exploiting this property, we present experimental results showing that the proposed method can offer a better tradeoff between time and frequency resolution, at the expense of some extra computations.

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Section: B Subband Model Designmentioning

confidence: 99%

Time–Frequency Synthesis of Noisy Sounds With Narrow Spectral Components

Marelli

Aramaki

Kronland‐Martinet

et al. 2010

IEEE Trans. Audio Speech Lang. Process.

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“…The OS, OA, ZDFC and LDFC methods, which we collectively call segmented fast Fourier transform (SFFT) methods, permit accommodating a trade-off between computational complexity and latency [8]. It was recently shown that a better trade-off can be achieved using a subband (SB) approximation of HRTFs [9], [10], if certain approximation tolerance can be allowed.…”

mentioning

confidence: 99%

Efficient Approximation of Head-Related Transfer Functions in Subbands for Accurate Sound Localization

Marelli

Baumgartner

Majdak

2015

IEEE/ACM Trans. Audio Speech Lang. Process.

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Head-related transfer functions (HRTFs) describe the acoustic filtering of incoming sounds by the human morphology and are essential for listeners to localize sound sources in virtual auditory displays. Since rendering complex virtual scenes is computationally demanding, we propose four algorithms for efficiently representing HRTFs in subbands, i.e., as an analysis filterbank (FB) followed by a transfer matrix and a synthesis FB. All four algorithms use sparse approximation procedures to minimize the computational complexity while maintaining perceptually relevant HRTF properties. The first two algorithms separately optimize the complexity of the transfer matrix associated to each HRTF for fixed FBs. The other two algorithms jointly optimize the FBs and transfer matrices for complete HRTF sets by two variants. The first variant aims at minimizing the complexity of the transfer matrices, while the second one does it for the FBs. Numerical experiments investigate the latency-complexity trade-off and show that the proposed methods offer significant computational savings when compared with other available approaches. Psychoacoustic localization experiments were modeled and conducted to find a reasonable approximation tolerance so that no significant localization performance degradation was introduced by the subband representation.Index Terms-Head-related transfer functions (HRTFs), subband signal processing, sparse approximation, sound localization, virtual acoustics.

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Adaptive control and signal processing literature survey (No. 18)

2010

Adaptive Control & Signal

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In order to keep readers up-to-date, the journal will contain a list of recently published journal articles relevant to the fields of adaptive control and signal processing six times a year. This list is compiled from a wide range of journals. Please note that although the list has been broadly categorized, these classifications are by no means strict, and are there to assist the reader. Please also note that inclusion in the list is not an endorsement of a paper's quality. If you have any suggestions or comments, please e-mail Erfu Yang at erfu.yang@eee.strath.ac.uk. ADAPTIVE SYSTEMSBaldi S, Battistelli G, Mosca E, Tesi P. Multi-model unfalsified adaptive switching supervisory control. Automatica 2010; 46(2):249-259. Cao C, Hovakimyan N. Stability margins of L 1 adaptive control architecture. IEEE Transactions on Automatic Control 2010; 55(2):480-487. Chen W, Jiao L. Adaptive tracking for periodically time-varying and nonlinearly parameterized systems using multilayer neural networks. IEEE Transactions on Neural Networks 2010; 21(2):345-351. Han T-T, Ge S, Lee T. Persistent dwell-time switched nonlinear systems: variation paradigm and gauge design. IEEE Transactions on Automatic Control 2010; 55(2):321-337. Li L, Petersen I. A Gramian-based approach to model reduction for uncertain systems. IEEE Transactions on Automatic Control 2010; 55(2):508-514. Li Q-K, Zhao J, Dimirovski G, Liu X-J. State convergence property of perturbed switched linear time-delay systems. IET Control Theory and Applications 2010; 4(2):273-281. Li T-S, Tong S-C, Feng G. A novel robust adaptive-fuzzytracking control for a class of nonlinear multi-input/multioutput systems. IEEE Transactions on Fuzzy Systems 2010; 18(1):150-160. Ma H-J, Yang G-H. Adaptive output control of uncertain nonlinear systems with non-symmetric dead-zone input. Automatica 2010; 46(2):413-420. Niedzwiecki M. Generalized adaptive notch smoothing revisited. IEEE Transactions on Signal Processing 2010; 58(3):1565-1576. Obaidat M, Misra S, Papadimitriou G. Adaptive and learning systems. IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetic 2010; 40(1):2-5. Yang Z-J, Hara S, Kanae S, Wada K, Su C-Y. An adaptive robust nonlinear motion controller combined with disturbance observer. IEEE Transactions on Control Systems Technology 2010; 18(2):454-462. Yildiz Y, Annaswamy A, Kolmanovsky L, Yanakiev D. Adaptive posicast controller for time-delay systems with relative degree n * 2. Automatica 2010; 46(2):279-289. Zhang W-A, Yu L. Stabilization of sampled-data control systems with control inputs missing. IEEE Transactions on Automatic Control 2010; 55(2):447-452. 2. SIGNAL PROCESSING Aboutanios E. Estimation of the frequency and decay factor of a decaying exponential in noise. IEEE Transactions on Signal Processing 2010; 58(2):501-509. Addesso P, Marano S, Matta V. Estimation of target location via likelihood approximation in sensor networks. IEEE Transactions on Signal Processing 2010; 58(3):1358-1368. Bai K, Tepedelenlioglu C. Distributed detection in UWB wireles...

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A Recursive Method for the Approximation of LTI Systems Using Subband Processing

Cited by 5 publications

References 29 publications

Time–Frequency Synthesis of Noisy Sounds With Narrow Spectral Components

Time–Frequency Synthesis of Noisy Sounds With Narrow Spectral Components

Efficient Approximation of Head-Related Transfer Functions in Subbands for Accurate Sound Localization

Adaptive control and signal processing literature survey (No. 18)

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