Titlebook: Neural Information Processing: Research and Development; Jagath Chandana Rajapakse,Lipo Wang Book 2004 Springer-Verlag Berlin Heidelberg 2

infection

書目名稱Neural Information Processing: Research and Development影響因子(影響力)




書目名稱Neural Information Processing: Research and Development影響因子(影響力)學(xué)科排名




書目名稱Neural Information Processing: Research and Development網(wǎng)絡(luò)公開度




書目名稱Neural Information Processing: Research and Development網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Neural Information Processing: Research and Development被引頻次




書目名稱Neural Information Processing: Research and Development被引頻次學(xué)科排名




書目名稱Neural Information Processing: Research and Development年度引用




書目名稱Neural Information Processing: Research and Development年度引用學(xué)科排名




書目名稱Neural Information Processing: Research and Development讀者反饋




書目名稱Neural Information Processing: Research and Development讀者反饋學(xué)科排名

FLIRT

Networks constructed of neuroid elements capable of temporal summation of signalsmultilevel processing of information. It is also shown that such a statistical analysis is used for textual information processing in the program TextAnalyst. (by Microsystems, Moscow), designed for the automatic semantic analysis of texts.

FIN

minion

On Some External Characteristics of Brain-like Learning and Some Logical Flaws of Connectionismtionism are not only logical flawed, but also are inconsistent with some commonly observed human learning behavior. The paper does not present any new learning algorithms, but it is about learning algorithms and what properties they should exhibit.

詞匯

Extension of Binary Neural Networks for Multi-class Output and Finite Automatae in the way of expressing a Finite Automaton (FA) in terms of recurrent BNNs. We prove that recurrent BNNs simulate any deterministic as well as non-deterministic finite automaton. The proof is constructive, and the construction process is illustrated by suitable examples.

縮影

Combination Strategies for Finding Optimal Neural Network Architecture and Weightsry complexity. The learning methodology has been tested using many benchmark databases such as XOR, 10 bit odd parity, handwriting characters from CEDAR, breast cancer and heart disease from UCI machine learning repository. The experimental results, detailed discussion and analysis are included in the chapter.

PALL

否決

A Method for Applying Neural Networks to Control of Nonlinear Systemslinear ARX model. The nonlinear controller is then designed in a similar way as designing a controller based on a linear ARX model. Numerical examples are used to illustrate the usefulness of the new method.

財(cái)政

絕種

Convolutional Spiking Neural Network for Robust Object Detection with Population Code Using Structur, end-stop, blob, eye, etc.). Introducing a population coding scheme in the CSNN architecture, we show how the biologically inspired model attains invariance to changes in size and position of face and ensures the efficiency of face detection.