An SVM based method for Associative Memories
نویسندگان
چکیده
The relation existing between support vector machines (SVMs) and recurrent associative memories is investigated. The design of associative memories based on the generalized brain-state-in-a-box (GBSB) neural model is formulated as a set of independent classification tasks, which can be efficiently solved by standard software packages for SVM learning. Some properties of the networks designed in this way are evidenced, like a surprising generalized Hebb’s law. The performance of the SVM approach is compared to existing methods with non-symmetric connections, by some design examples. Key-Words: Associative memories, neural networks, support vector machines.
منابع مشابه
A new Algorithm for Implementing BSB-based Associative Memories
The relation existing between support vector machines (SVMs) and recurrent associative memories is investigated. The design of associative memories based on the generalized brain-state-in-a-box (GBSB) neural model is formulated as a set of independent classification tasks, which can be efficiently solved by standard software packages for SVM learning. Some properties of the networks designed in...
متن کاملNo Rounding Reverse Fuzzy Morphological Associative Memories
The fuzzy morphological associative memories (FMAM) have many attractive advantages, but their recall effects for hetero associative memories are poor. This shortcoming impedes the application of hetero-FMAM. Aiming at the problem, and inspired by the unified framework of morphological associative memories, a new method called no rounding reverse fuzzy morphological associative memories (NRFMAM...
متن کاملNeural Network Applications F1.4 Associative memory
This section considers how neural networks can be used as associative memory devices. It first describes what an associative memory is, and then moves on to describe associative memories based on feedforward neural networks and associative memories based on recurrent networks. The section also describes associative memory systems based on cognitive models. It also highlights the ability of neur...
متن کاملA Design Method of Cellular Neural Networks for Associative Memories based on Linear Programming
A novel design method of cellular neural networks (CNNs) for associative memories is presented. The proposed method can realize as high recall probability as the method based on generalized eigenvalue minimization (GEVM), which is known as the most efficient CNN design method so far. On the other hand, since the proposed method is based on linear programming, its computation time is much shorte...
متن کاملModified Memory Convergence with Fuzzy PSO
Associative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this paper, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. An FPSO ...
متن کامل