Multistability and Instability of Competitive Neural Networks with Mexican-Hat-Type Activation Functions
نویسندگان
چکیده
منابع مشابه
Multistability and instability of delayed competitive neural networks with nondecreasing piecewise linear activation functions
In this paper, we investigate the exact existence and dynamical behaviors of multiple equilibrium points for delayed competitive neural networks (DCNNs) with a class of nondecreasing piecewise linear activation functions with 2rðr≥1Þ corner points. It is shown that under some conditions, the N-neuron DCNNs can have and only have ð2r þ 1Þ equilibrium points, ðr þ 1Þ of which are locally exponent...
متن کاملPersistent Activation Blobs in Spiking Neural Networks with Mexican Hat Connectivity
Abstract. Short range excitation, long range inhibition sometimes referred to as mexican hat connectivity seems to play important role in organization of the cortex, leading to fairly well delineated sites of activation. In this paper we study a computational model of a grid filled with rather simple spiking neurons with mexican hat connectivity. The simulation shows, that when stimulated with ...
متن کاملStochastic Neural Networks with Monotonic Activation Functions
We propose a Laplace approximation that creates a stochastic unit from any smooth monotonic activation function, using only Gaussian noise. This paper investigates the application of this stochastic approximation in training a family of Restricted Boltzmann Machines (RBM) that are closely linked to Bregman divergences. This family, that we call exponential family RBM (Exp-RBM), is a subset of t...
متن کاملDeep Neural Networks with Multistate Activation Functions
We propose multistate activation functions (MSAFs) for deep neural networks (DNNs). These MSAFs are new kinds of activation functions which are capable of representing more than two states, including the N-order MSAFs and the symmetrical MSAF. DNNs with these MSAFs can be trained via conventional Stochastic Gradient Descent (SGD) as well as mean-normalised SGD. We also discuss how these MSAFs p...
متن کاملQuadratic-Type Lyapunov Functions for Competitive Neural Networks with Different Time-Scales
The dynamics of complex neural networks modelling the selforganization process in cortical maps must include the aspects of long and short-term memory. The behaviour of the network is such characterized by an equation of neural activity as a fast phenomenon and an equation of synaptic modification as a slow part of the neural system. We present a quadratic-type Lyapunov function for the flow of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Abstract and Applied Analysis
سال: 2014
ISSN: 1085-3375,1687-0409
DOI: 10.1155/2014/901519