In this paper, some sufficient conditions for the local and global exponential stability of the discrete-time Hopfield neural networks with general activation functions are derived, which generalize those existing results. By means of M-matrix theory and some inequality analysis techniques, the exponential convergence rate of the neural networks to the equilibrium is estimated, and for the loca...

In this article, we discuss anti-periodic oscillations of BAM neural networks with leakage delays. A sufficient criterion guaranteeing the existence and exponential stability of the involved model is presented by utilizing mathematic analysis methods and Lyapunov ideas. The theoretical results of this article are novel and are a key supplement to some earlier studies.

Recently different approaches have been developed in the field of sensor fault diagnostics based on Auto-Associative Neural Network (AANN). In this paper we present a novel algorithm called Self reconstructing Auto-Associative Neural Network (S-AANN) which is able to detect and isolate single faulty sensor via reconstruction. We have also extended the algorithm to be applicable in multiple faul...

The brain must robustly store a large number of memories, corresponding to the many events and scenes a person encounters over a lifetime. However, the number of memory states in existing neural network models either grows weakly with network size or recall performance fails catastrophically with vanishingly little noise. Here we show that it is possible to construct an associative content-addr...

In several fields there is a divide between formal and associative models of concepts and reasoning. For example, in AI associative models such as neural networks and evolutionary computation are distinguished from symbolic, logic-based approaches. In psychology, fuzzy or category-based approaches compete with the “classical” theory of classification. In information science, systems based on dy...

The first description of ANN integrated circuit implements a continuous time analog circuit for AM. The design used a 22 x 22 matrix with 20,000 transistors, averaging 40 transistors per node to implement a Hopfield AM network. The design faced a scalability challenge at higher levels of integration. The paper advocates handling larger problems by a collection of smaller networks or hierarchica...

The content-addressability of random patterns stored in neural networks trained with iterative learning rules is studied numerically under the eeects of synaptic damage. The model of damage is random dilution of couplings with some probability after learning. A simple model based on the distribution of stabilities () is proposed, which allows for the calculation of the storage and retrieval pro...

In section 2, a definition of “trend” is given. In section 3, it is shown how to detect a trend using an auto-associative neural network. Experimental methods and results are reported in sections 4 and 5, and concluding remarks are given in section 6. Abstract — This paper reports the results of a new neural network based trend detector. An auto-associative neural network was trained with the “...