A neural network architecture for detecting moving objects. II

IEEE International Workshop on Cellular Neural Networks and their Applications Pub Date : 1990-12-16 DOI:10.1109/CNNA.1990.207515

V. Cimagalli

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引用次数: 5

Abstract

For pt.I see Proc. of the 3rd Italian Workshop of Parallel Architectures and Neural Networks. Summary form only given. In pt.I the author proposed an architecture for solving a problem of processing time-varying inputs. In that architecture, the signal is processed in a spatio-temporal dimension. Time is not the independent variable in the solution of a set of differential equations as in the classical case, but it plays an essential role in the interaction on the time-varying input and its processing. The purpose of the net is not, as usually, to classify and/or recognize patterns, nor to solve a problem of minimum energy, but to detect some characteristics of a signal varying with respect both to time and space. Such a network has been proved useful in solving the problem of detecting moving objects in a cluster. In this part, the architecture of the net is outlined and its performance is discussed together with its similarities and differences with respect to cellular neural networks. Results of computer simulations are given and the problem of hardware implementation is considered.<>

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一种用于运动物体检测的神经网络结构。2

参见第三届意大利并行架构与神经网络研讨会论文集。只提供摘要形式。在第一部分中，作者提出了一种解决时变输入处理问题的体系结构。在该体系结构中，信号在时空维度上进行处理。在微分方程解中，时间不是经典情况下的自变量，但在时变输入及其处理的相互作用中起着至关重要的作用。网络的目的不是像通常那样分类和/或识别模式，也不是解决能量最小的问题，而是检测信号随时间和空间变化的某些特征。这种网络已被证明在解决集群中运动物体的检测问题上是有用的。在这一部分中，概述了网络的结构，并讨论了它的性能以及它与细胞神经网络的异同。给出了计算机仿真结果，并考虑了硬件实现问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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IEEE International Workshop on Cellular Neural Networks and their Applications

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