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Abstract
Filter decomposition approach has been presented for multichannel blind deconvolution of non-minimum phase systems [12]. In this paper, we present a flexible cascade structure by decomposing the demixing filter into a casual finite impulse response (FIR) filter and an anti-causal scalar FIR filter. Subsequently, we develop the natural gradient algorithms for both filters. Computer simulations show good learning performance of this method.
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References
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Authors and Affiliations
Department of Computer Science and Engineering, Shanghai Jiaotong University Shanghai, China
Bin Xia & Liqing Zhang
- Bin Xia
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- Liqing Zhang
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Editor information
Editors and Affiliations
Indian Statistical Institute, Electronics and Communication Sciences Unit, Kolkata, India
Nikhil Ranjan Pal
School of Computer and Information Sciences, Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, Private Bag 92006, Auckland, New Zealand
Nik Kasabov
Department of Instrumentation and Electronics Engineering, Jadavpur University, Salt-lake Campus, 700098, Calcutta, India
Rajani K. Mudi
Indian Statistical Institute, 203 B. T. Road, 700 108, Calcutta,
Srimanta Pal
Indian Statistical Institute, Computer Vision and Pattern Recognition Unit, 700108, Kolkata, India
Swapan Kumar Parui
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Xia, B., Zhang, L. (2004). Multichannel Blind Deconvolution of Non-minimum Phase System Using Cascade Structure. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_184
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