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Based on the assumption that there are short periods of time in which only one source is active, a new approach for convolutive blind source separation (quasi-BSS) is proposed, which does not require the signals to be independent or identically distributed. In order to obtain a low-complexity iterative solution to the separation filters, an optimization method based on the affine projection adaptation...
This paper proposes a two-stage dereverberation algorithm with integrated reverberation and noise estimation. In the first stage, an inverse filter to the room impulse response suppresses reverberation by early reflections. Minimum mean-square error short-time spectral amplitude estimator in the second stage minimizes influence of both late reflections and ambient noise, simultaneously. Due to this...
In this paper, recent DSP studies performed by B.S. and M.S. students in the laboratory are presented. Processing using frequency domain samples and its implementation on TI DSK are emphasized. Recently, frequency domain samples were used in multiple beam satellite onboard processing for channelization, routing and digital beam forming. These procedures are very effective for the system which necessitate...
For many applications fixed-point DSPs are advantageous because of their comparatively low chip-size, power consumption and overall cost. On the other hand, due to the reduced dynamic range (compared to floating point devices) scaling is often necessary. This leads to an increased software development effort. Furthermore, the choice of a suitable filter structure is much more critical for fixed-point...
A particle filter based algorithm was developed to track vehicles in a network of roads under the assumption of sporadic and non-persistent sensor data. It is assumed we have a number of sensors that provide position and velocity information only, which are scattered at possibly uneven intervals throughout the road system of interest. Further, the sensor ranges do not overlap, meaning we do not have...
In order to provide a guideline to designers of practical adaptation systems that are based on the family of affine projection algorithms, this paper derives and verifies certain simple formulation for learning curves of relaxed and non-relaxed affine projection algorithms (APAs), to which the fast affine projection (FAP) algorithms approximate. It is observed that the formulation accurately predicts...
We give an overview of the algebraic signal processing theory, a recently proposed generalization of linear signal processing (SP). Algebraic SP (ASP) is built axiomatically on top of the concept of a signal model, which is a triple (A, M, Phi), where A is a chosen algebra of filters, M an associated A-module of signals, and Phi generalizes the idea of a z-transform. ASP encompasses standard time...
A summary of results from linear algebra pertaining to orthogonal projections onto subspaces of an inner product space is presented. A formal definition and a sufficient condition for the existence of a fractional transform given a unitary periodic operator is given. Next, using an orthogonal projection formula the class of weighted discrete fractional Fourier transforms (WDFrFTs) is shown to be completely...
The frequency domain Newton algorithm was introduced by Elliott and Rafaely in an effort to improve the convergence speed as well as to generate an unbiased steady-state solution for the case of a strict causality-constrained adaptive filter. However, their proposed frequency domain Newton algorithm requires that we split the normalized convergence coefficients into constituent causal and non-causal...
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