【摘要】 利用级联神经网络模型对多个三维目标进行识别 ,为提高其正确识别率 ,提出多种优化方法 ,它们可单独使用 ,也可以联合使用。对不变性编码、算法、互连权重的二值化方法、样本优选等进行了研究和探讨。利用优化后的模型对三个飞机模型在视场内的任意位置、任意取向 (面内旋转 36 0° ,面外旋转大于 45°)的投影进行识别。计算机模拟表明正确识别率达到 96 %以上。更多还原

【Abstract】 The cascaded neuron network model is used to recognize 3 D targets. In order to improve the recognizing rate, several methods of choosing the construct and algorithm are proposed. They can be used together or solely according to the requirement. The invariance encoding, the algorithm, the binarizing of the interconnection weights and the selecting methods of the training samples, and so on are studied. The computer simulation of recognizing three plane models is completed based on this cascaded neuron network model. The recognizing rate of the model is over 96% as the three planes arbitrarily positioned and directed.更多还原