optical processor architectures for various forms of the alternating projection neuralnetwork (APNN) are considered. Required iteration is performed by passive optical feedback using only free space and guided propag...
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In order to produce well-focused images of moving targets using radar, distortions in the radar echos due to the target's motion should be compensated for. Techniques exist to compensate distortion due to a target...
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The performance of neuralnetworks used for pattern recognition and classification may be improved by introducing some capacity for invariance into the network. Two measures of similarity and their relationship to the...
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Electronic competiton for a fixed current resource can be used to mediate a winner-take-all operation on an array of optical beams, using a special-purpose optoelectronic integrated circuit containing modulators and d...
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Partitioning of an object into N parts and the use of M filters with different output patterns are used to produce an NM digit symbolic encoding of the input object. The rule based system and techniques to update part...
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Binary pattern classification that may be implemented using optical hardware and neuralnetwork algorithms is considered. Pattern classification problems that have no concise description (as in classifying handwritten...
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The remarkable processing capabilities of the nervous system must derive at least in part from the large numbers of neurons participating (roughly 1010), since the timescales involved are of the order of milliseconds,...
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The remarkable processing capabilities of the nervous system must derive at least in part from the large numbers of neurons participating (roughly 1010), since the timescales involved are of the order of milliseconds, rather than the nanoseconds of modern computers. We summarise common features of the neuralnetworkmodels which attempt to capture this behaviour and describe the many levels of parallelism which they exhibit. A range of models has been implemented on the SIMD (ICL Distributed Array Processor) and MIMD (Meiko computing Surface) hardware at Edinburgh. Examples include: (i) training algorithms in the context of the Hopfield net, with specific application to the storage of words and text with content-addressable memory; (ii) the back-propagation training algorithm for the multi-layer perception; (iii) image restoration with Hopfield and Tank analogue neurons, and (iv) the Durbin and Willshaw elastic net, as applied to the travelling salesman problem.
To us, and to other biological organisms, vision seems effortless. We open our eyes and we "see" the world in all its color; brightness, and movement. Yet, we havegreat difficulties when trying to endow our ...
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To us, and to other biological organisms, vision seems effortless. We open our eyes and we "see" the world in all its color; brightness, and movement. Yet, we havegreat difficulties when trying to endow our machines with similar abilities. In this paper we shall describe recent developments in the theory of early vision which lead from the formulation of the motion problem as an ill-posed one to its solution by minimizing certain "cost" functions. These cost or energy functions can be mapped onto simple analog and digital resistive networks. Thus, we shall see how the optical flow can be computed by injecting currents into resistive networks and recording the resulting stationary voltage distribution at each node. These networks can be implemented in cMOS VLSI circuits and represent plausible candidates for biological vision systems. This manuscript is a condensed version of ref.' .
We describe an optoelectronic resonator associative memory system which utilizes holographic interconnects. Image processing techniques are used to implement non I inearities and feedback. We show using numerical mode...
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We consider various associative processor modifications required to allow these systems to be used for visual perception, scene analysis, and object recognition. For these applications, decisions on the class of the o...
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