We show that macro-molecular self-assembly can recognize and classify high-dimensional patterns in the concentrations of N distinct molecular species. Similar to associative neural networks, the recognition here leverages dynamical attractors to recognize and reconstruct partially corrupted patterns. Traditional parameters of pattern recognition theory, such as sparsity, fidelity, and capacity ...

Recent advances in associative memory design through strutured pattern sets and graph-based inference algorithms have allowed the reliable learning and retrieval of an exponential number of patterns. Both these and classical associative memories, however, have assumed internally noiseless computational nodes. This paper considers the setting when internal computations are also noisy. Even if al...

This paper considers the robust stability of neural networks with multiple delays. Based on Lyapunov stability theory and linear matrix inequality technique, some new delay independent conditions are derived to guarantee the global robust exponential stability of the equilibrium point. Furthermore, the obtained results are generalized to the interval neural networks and bidirectional associativ...

In associative memory, recall is based on similarity to a cue. With its inherent data parallelism, associative memory naturally lends itself to implementation on massively parallel hardware; it is our thesis that associative processing can serve as the basis of AI systems. We believe that the associative paradigm can encompass both neural network and symbolic applications. Current research indi...

There have been a lot of researches which apply evolutionary techniques to layered neural networks. However, their applications to Hop eld neural networks remain few so far. We have been applying a genetic algorithm to fully connected associative memory model of Hop eld, and reported elsewhere that the network can store some number of patterns only by evolving weight matrices with the genetic a...

Face classification is an important area of research with many applications, including biometric security and searching face databases. This article describes an approach to verify faces using Auto-associative Neural Networks and Eigenbands fusion. In Eigenbands strategy each faces is divided in horizontal bands from which are extracted features using PCA. This method aims capture discriminativ...

Abstract—In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with mixed delays is investigated. On the basis of Lyapunov stability theory and contraction mapping theorem, some new sufficient conditions are established for the existence and uniqueness and globally exponential stability of equilibrium, which generalize and improve the previously known res...

This paper deals with the problem of delay-dependent asymptotically stability for stochastic bidirectional associative memory neural networks with time-varying structured uncertainties and time-varying delays. The parameter uncertainties are assumed to be norm bounded. Based on a Lyapunov-Krasovskii functional and the stochastic stability analysis theory, new delay-dependent stability criteria ...

In this paper, we explore the recognition of polyphone. The cognition process is complex, which needs other additional information, otherwise it may cause uncertainty in decision. Recent research is almost focused on phonetics, while we plan to explore the question with neural networks. H. Haken used synergetic neural network to discuss the recognition of ambivalent patterns and the evolution e...