Download Advances in Neural Networks - ISNN 2008: 5th International by Ling Zou, Renlai Zhou, Senqi Hu, Jing Zhang, Yansong Li PDF

By Ling Zou, Renlai Zhou, Senqi Hu, Jing Zhang, Yansong Li (auth.), Fuchun Sun, Jianwei Zhang, Ying Tan, Jinde Cao, Wen Yu (eds.)

ISBN-10: 3540877312

ISBN-13: 9783540877318

The quantity set LNCS 5263/5264 constitutes the refereed complaints of the fifth overseas Symposium on Neural Networks, ISNN 2008, held in Beijing, China in September 2008.

The 192 revised papers offered have been conscientiously reviewed and chosen from a complete of 522 submissions. The papers are equipped in topical sections on computational neuroscience; cognitive technology; mathematical modeling of neural platforms; balance and nonlinear research; feedforward and fuzzy neural networks; probabilistic equipment; supervised studying; unsupervised studying; help vector computer and kernel tools; hybrid optimisation algorithms; laptop studying and knowledge mining; clever regulate and robotics; development popularity; audio photo processinc and computing device imaginative and prescient; fault prognosis; functions and implementations; purposes of neural networks in digital engineering; mobile neural networks and complex keep watch over with neural networks; nature encouraged tools of high-dimensional discrete facts research; development attractiveness and data processing utilizing neural networks.

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Read or Download Advances in Neural Networks - ISNN 2008: 5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I PDF

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Extra resources for Advances in Neural Networks - ISNN 2008: 5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I

Example text

In order to capture an adequate proportion of the signal energy, the theta band was also included into the analysis. Combined, the delta and theta band preserve 77% of the signal energy at site PO3. e. at least two thirds) of the signal energy at all electrodes sites. The delta band corresponded to the approximation level (a6) of the MRA while the theta band corresponded to the highest detail level (d6). All activity from frequency bands higher than the theta band was suppressed by setting corresponding wavelet coefficients to zero and subsequent inverse transform to the time domain.

Met. cn Abstract. Nonnegative tensor factorization is an extension of nonnegative matrix factorization(NMF) to a multilinear case, where nonnegative constraints are imposed on the PARAFAC/Tucker model. In this paper, to identify speaker from a noisy environment, we propose a new method based on PARAFAC model called constrained Nonnegative Tensor Factorization (cNTF). Speech signal is encoded as a general higher order tensor in order to learn the basis functions from multiple interrelated feature subspaces.

In: IEEE International Conference on ICASSP 1979, vol. 4, pp. 208–211 (1979) 6. : A Review of Signal Subspace Speech Enhancement and Its Application to Noise Robust Speech Recognition. EURASIP Journal on Applied Signal Processing 1, 195–209 (2007) 7. : Efficient Auditory Coding. Nature 439, 978–982 (2006) 8. : Learning Self-organized Topology-preserving Complex Speech Features at Primary Auditory Cortex. Neurocomputing 65, 793–800 (2005) 9. : Nonnegative Features of Spectro-temporal Sounds for Classification.

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