A Novel Multivalued Associative Memory System

Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.

Context query and association discovery for collaborative environment

A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collaborative associations, an approach of transforming RDF named graphs into ＂context graph＂ is proposed. First, the definitions of the importance of the nodes and the weight assignment for the ＂context graph＂ are given. Secondly, the implementation of a spread activation algorithm based on ＂context graph＂ is proposed. An infrastructure is also built up in the collaborative context space （CCS） system to support context memory and knowledge discovery in a collaborative environment.

DISCRETE BIDIRECTIONAL ASSOCIATIVE MEMORY WITH LEARNING FUNCTION

In this paper we propose a new discrete bidirectional associative memory (DBAM) which is derived from our previous continuous linear bidirectional associative memory (LBAM). The DBAM performs bidirectionally the optimal associative mapping proposed by Kohonen. Like LBAM and NBAM proposed by one of the present authors,the present BAM ensures the guaranteed recall of all stored patterns,and possesses far higher capacity compared with other existing BAMs,and like NBAM, has the strong ability to suppress the noise occurring in the output patterns and therefore reduce largely the spurious patterns. The derivation of DBAM is given and the stability of DBAM is proved. We also derive a learning algorithm for DBAM,which has iterative form and make the network learn new patterns easily. Compared with NBAM the present BAM can be easily implemented by software.

BIDIRECTIONAL ASSOCIATIVE MEMORY ENSEMBLE

The multiple classifier system （MCS）, composed of multiple diverse classifiers or feed-forward neural networks, can significantly improve the classification or generalization ability of a single classifier. Enlightened by the fundamental idea of MCS, the ensemble is introduced into the quick learning for bidirectional associative memory （QLBAM） to construct a BAM ensemble, for improving the storage capacity and the error-correction capability without destroying the simple structure of the component BAM. Simulations show that, with an appropriate ＂overproduce and choose＂ strategy or ＂thinning＂ algorithm, the proposed BAM ensemble significantly outperforms the single QLBAM in both storage capacity and noise-tolerance capability.

STABILITY OF BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH DELAYS

In this paper the globally asymptotic stability of more general two-layer nonlinear feedback associative memory neural networks with time delays is examined. The sufficient conditions of existence, uniqueness and globally asymptotic stability of the equilibrum position are given. Finally, two interesting examples to illustrate the theory are given.

QUALITATIVE ANALYSIS OF BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS

In this paper, the global exponential stability of an equilibrium position for general bidirectional associative memory neural networks are studied. The sufficient conditions of existence and uniqueness of the equilibrium position are given. The method of energy function is examined. Two examples are given to illustrate the theory.

Multi-Valued Associative Memory Neural Network

A novel learning method for multi-valued associative memory network is introduced, which is based on Hebb rule, but utilizes more information. According to the current probe vector, the connection weights matrix could be chosen dynamically. Double-valued and multi-valued associative memory are all realized in our simulation experiment. The experimental results show that the method could enhance the associative success rate.

CHAOTIC NEURAL NETWORK FOR ASSOCIATIVE MEMORY

Based on current research on applications of chaotic neuron network for information processing, the stability and convergence of chaotic neuron network are proved from the viewpoint of energy function. Moreover, a new auto-associative matrix is devised for artificial neural network composed of chaotic neurons, thus, an improved chaotic neuron network for associative memory is built up. Finally, the associative recalling process of the network is analyzed in detail and explanations of improvement are given.

ESTIMATION OF ATTRACTION DOMAIN AND EXPONENTIAL CONVERGENCE RATE OF CONTINUOUS FEEDBACK ASSOCIATIVE MEMORY AND ITS APPLICATIONS

The attraction domains of memory patterns and exponential convergence rate of the network trajectories to memory patterns for continuous feedback associative memory are estimated. These results can be used for evaluation of error-correction capability and the synthesis procedures for continuous-time associative memory neural networks.

Perspective in Development of Shape Memory Materials Associated with Martensitic Transformation

By consideration of the characteristics of martensitic transformation and the derivation from the application of the group theory to martensitic transformation, it may be concluded that the shape memory effect (SME) can be attained in materials through a martensitic transformation and its reverse transformation. only when there forms single or nearly single variant of martensite, with an absence of the factors causing the generation of the resistance against SME. on this principle, various shape memory materials including nonferrous alloys. iron-based alloys and ceramics containjng zirconia are expected to be further developed. A criterion for thermoelastic martensitic transformation is presented, Factors which may act as the resistance against SME in various materials are briefly described

Changes of learning and memory ability associated with neuronal nitric oxide synthase in brain tissues of rats with acute alcoholism

BACKGROUD： Ethanol can influence neural development and the ability of leaming and memory, but its mechanism of the neural toxicity is not clear till now. Endogenous nitric oxide （NO） as a gaseous messenger is proved to play an important role in the formation of synaptic plasticity, transference of neuronal information and the neural development, but excessive nitro oxide can result in neurotoxicity. OBJECTIVE ： To observe the effects of acute alcoholism on the learning and memory ability and the content of neuronal nitric oxide synthase （nNOS） in brain tissue of rats. DESIGN ： A randomized controlled animal experiment. SETTING ： Department of Physiology, Xinxiang Medical College MATERIALS： Eighteen male clean-degree SD rats of 18-22 weeks were raised adaptively for 2 days, and then randomly divided into control group （n = 8） and experimental group （n = 10）. The nNOS immunohistochemical reagent was provided by Beijing Zhongshan Golden Bridge Biotechnology Co.,Ltd. Y-maze was produced by Suixi Zhenghua Apparatus Plant. METHODS ： The experiment was carded out in the laboratory of the Department of Physiology, Xinxiang Medical College from June to October in 2005. ① Rats in the experimental group were intraperitoneally injected with ethanol （2.5 g/kg） which was dissolved in normal saline （20%）. The loss of righting reflex and ataxia within 5 minutes indicated the successful model. Whereas rats in the control group were given saline of the same volume. ② Examinations of learning and memory ability： The Y-maze tests for learning and memory ability were performed at 6 hours after the models establishment. The rats were put into the Y-maze separately. The test was performed in a quiet and dark room. There was a lamp at the end of each of three pathways in Y-maze and the base of maze had electric net. All the lamps of the three pathways were turned on for 3 minutes and then turned off. One lamp was turned on randomly, and the other two delayed automatically. In 5 seconds after alternation, pulsating electric current presented in the base of unsafe area to stimulate rat＇s feet to run to the safe area. The lighting lasted for 15 seconds as one test. Running from unsafe area to safe area at one time in 10 seconds was justified as successful. Such test was repeated for 10 times for each rat and the successful frequency was recorded. The qualified standard of maze test was that the rat ardved in the safe area g times during 10 experiments. The number of trainings for the qualified standard was used to represent the result of spatial learning. ③ Determination of the content of nNOS in brain tissue： After the Y-maze test, the rats were anaesthetized, and blood was let from the incision on right auricle, transcardially perfused via the left ventricle with about 200 mL saline, then fixed by perfusion of 40 g/L paraformaldehyde. Hippocampal CA1 region, corpus striatum and cerebellum were taken to prepare serial freezing coronal sections. The nNOS contents in the brain regions were determined with the immunohistochemical methods to reflect the changes of nitdc oxide in brain tissue. MAIN OUTCOME MEASURES ： The changes of learning and memory ability and the changes of the nNOS contents in the brain tissue of rats with acute alcoholism were observed. RESULTS ： One rat in the experimental group was excluded due to its slow reaction to electdc stimulation in the Y-maze test, and the other 17 rats were involved in the analysis of results. ① The training times to reach qualifying standards of Y-maze in the expedmental group was more than that in the control group [（34.33 ±13.04）, （27.50±8.79） times, P〈 0.05]. ② Forms and numbers of nNOS positive neurons in brain tissue： It could be observed under light microscope that in the hippocampal CA1 region, there were fewer nNOS positive neurons, which were lightly stained, and the processes were not clear enough; But the numbers of the positive neurons which were deeply stained as huffy were obviously increased in the experimental group, the cell body and cyloplasm of process were evenly stained, but the nucleus was not stained. The nNOS positive neurons in corpus stdatum had similar forms and size in the experimental group and control group. The form of the nNOS positive neurons in cerebellum were similar between the two groups. The numbers of nNOS positive neurons in hippocampal CA1 region and corpus striatum in the expedmental group [（18.22±7.47）, （11.38±5.00） cells/high power field] were obviously higher than those in the control group [（10.15±4.24）, （6.15±3.69） cells/high power field. The number of nNOS positive neurons in cerebellum had no significant difference between the two groups [（49.56±18.84）, （44.43±15.42） cells/high power field, P〉 0.05]. CONCLUSION ： Acute alcoholism may impair learning and memory ability, and nitric oxide may be involved in mediating the neurotoxic role of ethanol.

Properties and Stability of Max-Product Fuzzy Bi-Directional Associative Memory

In this paper, a fuzzy operator of max-product is defined at first, and the fuzzy bi-directional associative memory (FBAM) based on the fuzzy operator of max-product is given. Then the properties and the Lyapunov stability of equilibriums of the networks are studied.

A UNIFIED BIDIRECTIONAL ASSOCIATIVEMEMORY MODEL

A unified bidirectional associative memory model (UBAM) isproposed- Its two special cases, UHOBAM and UEBAM, are the modifica-tions of intraconnected BAM (IBAM) and higher-order BAM (HOBAM),exponential BAM (EBAM) and modified exponential BAM (MEBAM) , re-

NEW EXPONENTIAL BIDIRECTIONAL ASSOCIATIVE MEMORY

A new exponential bidirectional associative memory model is introduced. It offers an even better recall performance than the modified exponential bidirectional associative memory (MEBAM). Only a little complexity of realization is spent for the improvement.

SOME STATISTICAL ANALYSIS OF THE RECALL PROBABILITY OF PARALLEL INTRACONNECTED BIDIRECTIONAL ASSOCIATIVE MEMORY

This paper addressed a statistical analysis for the recall of parallel intraconnected bidirectional associative memory-Modified Intraconnected Bidirectional Associative Memory (MIBAM) and proved the conclusions: two MIBAM with the equal total number of neurons have the equal recalling probability for m pairs of stored pattern pairs if m is not too large. So they have the same capacity and same error correcting ability, i. e., their performances are statistically equivalent. The results of simulation support the conclusions well.

Comments on″Capacity Analysis of the Asymptotically Stable Multi-Valued Exponential Bidirectinal Associative Memory″

Asymptotical stability is an important property of the associative memory neural networks.In this comment,we demonstrate that the asymptotical stability analyses of the MVECAM and MV-eBAM in the asynchronous update mode by Wang et al are not rigorous,and then we modify the errors and further prove that the two models are all asymptotically stable in both synchronous and asynchronous update modes.

Double-pattern associative memory neural network with pattern loop

A double-pattern associative memory neural network with “pattern loop” is proposed. It can store 2N bit bipolar binary patterns up to the order of 2 2N , retrieve part or all of the stored patterns which all have the minimum Hamming distance with input pattern, completely eliminate spurious patterns, and has higher storing efficiency and reliability than conventional associative memory. The length of a pattern stored in this associative memory can be easily extended from 2N to kN.

A NEW BIDIRECTIONAL ASSOCIATIVE MEMORY MODEL-HOMIBAM

A new bidirectional associative memory model named as HOMIBAM is introduced. The relationships of HOMIBAM with the models existed are pointed out. Both theoretical analysis and simulations show that the capacity and recall performance of HOMIBAM are superior to that of modified intraconnected BAM (MIBAM), higher-order BAM (HOBAM ) greatly.

GLOBAL DYNAMICS OF DELAYED BIDIRECTIONAL ASSOCIATIVE MEMORY (BAM) NEURAL NETWORKS

Without assuming the smoothness,monotonicity and boundedness of the activation functions, some novel criteria on the existence and global exponential stability of equilibrium point for delayed bidirectional associative memory (BAM) neural networks are established by applying the Liapunov functional methods and matrix_algebraic techniques. It is shown that the new conditions presented in terms of a nonsingular M matrix described by the networks parameters,the connection matrix and the Lipschitz constant of the activation functions,are not only simple and practical,but also easier to check and less conservative than those imposed by similar results in recent literature.