由于受第一次并行分布处理(Parallel Distributed Processing)浪潮的影响,早期的神经网络研究偏重于采用单个复杂的大网络来解决问题,认为知识的表示越 分布越好。
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这个领域 有很多术语,例如连接机制、并行分布处理、神经计算、自然 智能系统、机器学习算法和人工神经网络。
The field goes by many names, such as connectionism, parallel distributed processing, neuro-computing, natural intelligent systems, machine learning algorithms, and artificial neural networks.
本文第三部分讨论了神经网络分类器的设计鉴于汽车识别问题的特性,充分利用神经网络的并行分布处理的特点,将神经网络算法用于汽车识别。
The third part of paper discusses the design of neural network group classifier, in view of speciality of vehicle recognition, neural network algorithms are applied to resolve the problem.
在上例中,关键数据是用户配置文件,可以跨一组机器分布(分区)以进行并行处理。
In the initial example above, the key data was user profiles, which could be distributed (partitioned) across a set of machines for parallel processing.
And the answer is, unlike many, unlike commercially generated computers, the brain works through parallel processing, massively parallel distributed processing.
问题的答案是这样的,与出于商业目的而制造的计算机不同,大脑采用并行加工的方式处理信息,采用广泛分布的并行加工
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