This paper proposes a general associative memory (GAM) system that combines the functions of other typical associative memory (AM) systems. The GAM is a network consisting of three layers: an input layer, a memory layer, and an associative layer. The input layer accepts key vectors, response vectors, and the associative relationships between these vectors. The memory layer stores the input vect...

Visual recognition requires connecting perceptual information with contextual information and existing knowledge. The ventromedial temporal cortex (VTC), including the medial fusiform, has been linked with object recognition, paired associate learning, contextual processing, and episodic memory, suggesting that this area may be critical in connecting visual processing, context, knowledge and ex...

The medial prefrontal cortex (mPFC) comprises an important component in the neural circuitry underlying drug-related associative learning and memory processing. Neuronal activation within mPFC circuits is correlated with the recall of opiate-related drug-taking experiences in both humans and other animals. Using an unbiased associative place conditioning procedure, we recorded mPFC neuronal pop...

One of the special types of Computer Memory is said to be as Content Addressable Memory. It is also called as associative array or associative storage, associative memory which can be frequently used in very high speed searching applications such as databases, associative computing, lookup tables and networking. CAM is one type of functional memory which contains huge amount of stored data wher...

We apply genetic algorithms to fully connected Hop eld associative memory networks. Previously, we reported that a genetic algorithm can evolve networks with random synaptic weights to store some number of patterns by pruning some of its synapses. The associative memory capacity obtained in that experiment was around 16% of the number of neurons. However the size of basin of attraction was rath...

This paper addresses the definition of the requirements for the design of a neural network associative memory, with on-chip training, in standard digital CMOS technology. We investigate various learning rules which are integrable in silicon, and we study the associative memory properties of the resulting networks. We also investigate the relationships between the architecture of the circuit and...

This paper proposes a neural network classifier which can automatically detect the occluded regions in the given image and replace that regions with the estimated values. An auto-associative memory is used to detect outliers such as pixels in the occluded regions. Certainties of each pixels are estimated by comparing the input pixels with the outputs of the auto-associative memory. The input va...