Titlebook: Advances in Independent Component Analysis; Mark Girolami Book 2000 Springer-Verlag London 2000 Ensembl.artificial intelligence.artificial

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書目名稱Advances in Independent Component Analysis影響因子(影響力)




書目名稱Advances in Independent Component Analysis影響因子(影響力)學(xué)科排名




書目名稱Advances in Independent Component Analysis網(wǎng)絡(luò)公開度




書目名稱Advances in Independent Component Analysis網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Advances in Independent Component Analysis被引頻次




書目名稱Advances in Independent Component Analysis被引頻次學(xué)科排名




書目名稱Advances in Independent Component Analysis年度引用




書目名稱Advances in Independent Component Analysis年度引用學(xué)科排名




書目名稱Advances in Independent Component Analysis讀者反饋




書目名稱Advances in Independent Component Analysis讀者反饋學(xué)科排名

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Detection of Chromothripsis in PlantsNetworks (ICANN99), the most prestigious ANN conference in Europe. However, as this book demonstrates, many of the methods currently being investigated by the neural network community are very different from the biologically-inspired networks which we will advocate.

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Ribosomal genes and nucleolar morphologymodels using a probabilistic ‘generative’ framework. In this paper, we follow this approach and combine hidden Markov models (HMM), Independent Component Analysis (ICA) and generalised autoregressive models (GAR) into a single generative model for the analysis of non-stationary multivariate time series.

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R. B. Dunn,J. B. Zirker,J. M. Beckersare then searched within each subspace. We present results of the algorithm on synthetic distributions with various degrees of degeneracy. Our results are promising for feature extraction applications.

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Book 2000ience and electrical engineering; research and development personnel in disciplines such as statistical modelling and data analysis; bio-informatic workers; and physicists and chemists requiring novel data analysis methods.

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