• Publications
  • Influence
A frequency domain method for blind source separation of convolutive audio mixtures
  • K. Rahbar, J. Reilly
  • Mathematics, Computer Science
  • IEEE Transactions on Speech and Audio Processing
  • 15 August 2005
TLDR
In this paper, we propose a new frequency domain approach to blind source separation (BSS) of audio signals mixed in a reverberant environment that exploits the inherent nonstationarity of the sources. Expand
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Statistical analysis of the performance of information theoretic criteria in the detection of the number of signals in array processing
TLDR
The performances of the Akaike (1974) information criterion and the minimum descriptive length criterion methods are examined. Expand
  • 129
  • 9
Radar design principles - Signal processing and the environment (2nd revised and enlarged edition)
TLDR
Radar and its composite environment radar range performance computations, statistical relationships for various detection processes, automatic detection by nonlinear, sequential and adaptive processes radar targets, propagation, sea and land scattering, signal processing concepts and waveform design, moving target indicators, environmental limitations of CW Radar, pulse doppler and burst waveforms, phase coding techniques, linear frequency modulated pulse compression waveforms. Expand
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The complex subband decomposition and its application to the decimation of large adaptive filtering problems
TLDR
We show that a near perfect reconstruction (NPR) M-channel filterbank with a diagonal system inserted between the analysis and synthesis filterbanks may be used to decompose a finite impulse response (FIR) system into M complex subband components, each of order L/K, where K is the downsampling rate. Expand
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Detection of the number of signals: a predicted eigen-threshold approach
TLDR
A novel method for detecting the number of signals incident upon an array of sensors is described. Expand
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An EM Algorithm for Nonlinear State Estimation With Model Uncertainties
TLDR
In most solutions to state estimation problems, e.g., target tracking, it is generally assumed that the state transition and measurement models are known a priori. Expand
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A machine learning approach using EEG data to predict response to SSRI treatment for major depressive disorder
OBJECTIVE The problem of identifying, in advance, the most effective treatment agent for various psychiatric conditions remains an elusive goal. To address this challenge, we investigate theExpand
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On information theoretic criteria for determining the number of signals in high resolution array processing
TLDR
An important problem in high-resolution array processing is the determination of the number of signals arriving at the array. Expand
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Efficient design of oversampled NPR GDFT filterbanks
TLDR
We propose a flexible, efficient design technique for the prototype filter of an oversampled near perfect reconstruction (NPR) generalized discrete Fourier transform (GDFT) filterbank. Expand
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Sizing of 3-D Arbitrary Defects Using Magnetic Flux Leakage Measurements
In this paper, we propose a new procedure to estimate the shape of the opening and the depth profile of an arbitrary three-dimensional (3-D) defect from magnetic flux leakage (MFL) measurements. WeExpand
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