The paper introduces a new control system that's fast, accurate and intelligent. Unlike traditional techniques used to date, this system works in the optical domain i.e. it is run on optical computers which are faster than the existing computers. The control system is a merger of optical computers, fuzzy logic, and neural networks. Possible application of genetic algorithms are also proposed which are very good at finding an optimal solution. This paper deals with the advantages of optical computing, need of fuzzy logic and essential merger with neural nets.

An intelligent adaptive fuzzy-neural control system for applications in hazardous environments

The advantage of optics is its capability of providing highly parallel operations in a three-dimensional space. In this paper, we propose optical architectures to execute various image compression techniques. We optically implement the following compression techniques: transform coding, vector quantization, video coding. We show many generally used transform coding methods, for example, the cosine transform, can be implemented by a simple optical system. The transform coding can be carried out in constant time. Most of this paper is concerned with an innovative optical system for vector quantization using holographic associative matching. Limitations of conventional vector quantization schemes are caused by a large number of sequential searches through a large vector space. Holographic associative matching provided by multiple exposure holograms can offer advantageous techniques for vector-quantization-based compression schemes. Photorefractive crystals, which provide high-density recording in real time, are used as our holographic media. The reconstruction alphabet can be dynamically constructed through training or stored in the photorefractive crystal in advance. Encoding a new vector can be carried out by holographic associative matching in constant time. An extension to interframe coding using optical block matching methods is also discussed. >

Optical computing techniques for image/video compression

A review of the contemporary issues in optical computing is presented. The optical systems and techniques which are used to implement different functional sub units of a digital computer are elaborated. Several architectures that are being explored for digital optical computing are described. Some issues relating to organisational and functional aspects of optical computing, such as cellular automata, symbolic substitution, optical artificial intelligence and optical neural network are also discussed.

An intelligent adaptive fuzzy-neural control system for applications in hazardous environments

References

Optical computing techniques for image/video compression

Optical Computing Techniques

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