*Correspondence: [email protected] 1Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China Full list of author information is available at the end of the article Abstract This paper investigates the impacts of state-dependent impulses on the stability of switching Cohe...

We have developed a neural network which consists of cooperatively interconnected Grossberg on-center off-surround subnets and which can be used to optimize a function related to the log likelihood function for decoding convolutional codes or more general FIR signal deconvolution problems. Connections in the network are confined to neighboring subnets, and it is representative of the types of n...

In this paper, without assuming strict positivity of amplifier functions, boundedness of activation functions, or symmetry of the connection matrix, dynamical behaviors of delayed Cohen-Grossberg neural networks with nonnegative equilibria are studied. Based on the theory of the nonlinear complementary problem (NCP), a sufficient condition is derived guaranteeing the existence and uniqueness of...

An important task in object recognition is to rst identify the boundaries of the objects in the input image. Several neural networks have been proposed to perform edge detection and boundary segmenta-tion. Among them, Grossberg and Mingolla's Boundary Contour System (BCS) seems promising because it is able to complete missing object boundaries. Although BCS has been shown to work well on synthe...

the proposed iafc neural networks have both stability and plasticity because theyuse a control structure similar to that of the art-1(adaptive resonance theory) neural network.the unsupervised iafc neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. this fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. the supervised iafc ...

Tom M. Heskes Bert Kappen Department of Medical Physics and Biophysics, University of Nijmegen, Geert Grooteplein Noord 21, 6525 EZ Nijmegen, The Netherlands, e-mail: [email protected] Abstract We study the learning dynamics of neural networks from a general point of view. The environment from which the network learns is de ned as a set of input stimuli. At discrete points in time, one of these ...