Artificial memories

Artificial Learning in Artificial Memories

Artificial Learning in Artificial Memories John Robert Burger Professor Emeritus Department of Electrical and Computer Engineering 25686 Dahlin Road Veneta, OR 97487 ([email protected]) Abstract – Memory refinements are designed below to detect those sequences of actions that have been repeated a given number n. Subsequently such sequences are permitted to run without CPU involvement. This mi...

Applied Artificial Neural Networks: from Associative Memories to Biomedical Applications

Due to remarkable capabilities of artificial neural networks (ANNs) such as generalization and nonlinear system modeling, ANNs have been extensively studied and applied in a wide variety of applications (Amiri et al., 2007; Davande et al., 2008). The rapid development of ANN technology in recent years has led to an entirely new approach for the solution of many data processing-based problems, u...

Neural networks as artificial memories for association rule mining

The collection of data is a high priority task in our daily life because humans are interested in understanding more about the variables of the diverse events happening around us. This analysis or understanding is derived from the usage of techniques which aim to produce predictive or descriptive models from data. While the former generates models to predict new status of data, the latter finds...

Memories

Synthesis of Neural Associative Memories for Artificial Vision Systems by Fuzzy Image Segmentations

A design procedure of neural associative memories to be used for robot vision systems is developed, which fits in the capabilities both of discrete-time cellular neural networks (DTCNNs) and fuzzy logic. The choice of this kind of neural networks is motivated by their architecture, suitable for storing images, and their locally connected structure, which is effective for the hardware implementa...