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11 This paper describes an algorithm called zero-crossing-based amplitude estimation (ZCAE) that enhances speech by reconstructing 12 the desired signal from a mixture of two signals using continuously-variable weighting factors, based on pre-processing that is motivated 13 by the well-known ability of the human auditory system to resolve(More)
Indexing terms: Digital signal processing, noisy speech recognition, independent component analysis, blind source separation A method for directly extracting clean speech features from noisy speech is proposed. This process is based on independent component analysis (ICA) and a new feature analysis technique to reduce the computational complexity of the(More)
An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in(More)
Indexing terms: Adaptive signal processing, independent component analysis, adaptive noise cancelling A method for adaptive noise cancelling based on independent component analysis (ICA) is presented. Although conventional least-mean-squares (LMS) algorithm removes noise components based on second-order correlation, the proposed algorithm can utilize(More)
Recently the camera resolution has been highly increased, and the registration between high-resolution images is computationally expensive even by using hierarchical block matching. This paper presents a novel optimized hierarchical block matching algorithm in which the computational cost is minimized for the scale factor and the number of levels in the(More)
It is well known that binaural processing is very useful for separating incoming sound sources as well as for improving the in-telligibility of speech in reverberant environments. This paper describes and compares a number of ways in which the classic model of interaural cross-correlation proposed by Jeffress, quantified by Colburn, and further elaborated(More)
We present a filter bank approach to perform independent component analysis (ICA) for convolved mixtures. Input signals are split into subband signals and subsampled. A simplified network performs ICA on the subsampled signals, and finally independent components are synthesized. The proposed approach achieves superior performance than the frequency domain(More)
This paper presents a new method of sound segregation based on zero-crossings generated from binaural filter-bank outputs. In our approach, sound source directions are identified using the spatial cues such as inter-aural time differences (ITDs) and inter-aural intensity differences (IIDs). The estimation of ITDs is performed using zero-crossings generated(More)