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Neural Networks
Pergamon Press, Inc.
 
   
 
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  1-10 of 37 reviews Date Reviewed 
  A generalized analog implementation of piecewise linear neuron models using CCII building blocks
Soleimani H., Ahmadi A., Bavandpour M., Sharifipoor O. Neural Networks 5126-38, 2014.  Type: Article

The second generation current conveyor (CCII) is becoming a popular design choice for analog very large-scale integration (VLSI) designs. This paper uses it for analog implementation of some piecewise linear neural models dubbed two po...

May 27 2014
  Direct kernel perceptron (DKP): ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation
Fernández-Delgado M., Cernadas E., Barro S., Ribeiro J., Neves J. Neural Networks 5060-71, 2014.  Type: Article

Categorized as supervised learning algorithms, margin-classification systems are often deployed to arrive at the decision boundary that separates different classes in a hyperplane. A new margin-classification method, direct kernel perc...

May 5 2014
  Cognitive memory
Widrow B., Aragon J. Neural Networks 413-14, 2013.  Type: Article

If you have basic knowledge of neural networks and are interested in building a new kind of computer memory that uses pattern recognition to return not only the recognized item but all related items, then this paper is for you....

Feb 25 2014
  Comparing error minimized extreme learning machines and support vector sequential feed-forward neural networks
Romero E., Alquézar R. Neural Networks 25122-129, 2012.  Type: Article

Error minimized extreme learning machines (EM-ELMs) were introduced to improve upon the learning time of feed-forward learning neural networks [1]. EM-ELMs are constructed by an incremental process that introduces hidden nodes into the...

Mar 2 2012
  Including cognitive biases and distance-based rewards in a connectionist model of complex problem solving
Dandurand F., Shultz T., Rey A. Neural Networks 2541-56, 2012.  Type: Article

Dandurand et al. have devised a computational model, and a way to train it, that better matches human performance on learning a certain problem-solving task than their previous model. The problem to be solved is to find which of 12 ite...

Mar 1 2012
  An architectural model of conscious and unconscious brain functions: global workspace theory and IDA
Baars B., Franklin S. Neural Networks 20(9): 955-961, 2007.  Type: Article

Baars has registered at least 25 years of active pursuit of “conscious contents” as “coherent, global information” in brain-like behavior. Global workspace theory (GWT) postulates that the role o...

Mar 4 2008
  Phenomenology and digital neural architectures
Aleksander I., Morton H. Neural Networks 20(9): 932-937, 2007.  Type: Article

What Aleksander and Morton call Axiomatic Consciousness Theory in this paper is an entry point into a program for constructing a neuroarchitectural model of visual phenomenology. The five axioms used deal with: the sensation of presenc...

Feb 20 2008
  Stochastic complexities of general mixture models in variational Bayesian learning
Watanabe K., Watanabe S. Neural Networks 20(2): 210-219, 2007.  Type: Article

In real-world problems, the probability distribution of a given data set usually has multiple modes. The probability distribution can be estimated as a mixture of single-mode distributions. A powerful method for estimating the mixture ...

Jun 15 2007
  The emergence of goals in a self-organizing network: a non-mentalist model of intentional actions
Louzoun Y., Atlan H. Neural Networks 20(2): 156-171, 2007.  Type: Article

Self-organization has been shown to exist for geometrical structures; that is, complex global spatiotemporal structures have been produced in nontrivial ways by relatively simple constraints, deterministic or stochastic, at the level o...

May 31 2007
  The role of short-term depression in sustained neural activity in the prefrontal cortex: a simulation study
Igarashi Y., Sakumura Y., Ishii S. Neural Networks 19(8): 1137-1152, 2006.  Type: Article

The neural mechanisms underlying memory retention and memory selection, both important ingredients of decision making, are studied via computer simulation of a biophysically realistic network model in this paper....

May 4 2007
 
 
 
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