公开(公告)号：US07324979B2

公开(公告)日：2008-01-29

申请号：US10652542

申请日：2003-08-29

申请人： Gary Dana Butler ,  Andrew Charles Coon ,  Robert Warren Kanyuck ,  Ernest Scott Stickels

发明人： Gary Dana Butler ,  Andrew Charles Coon ,  Robert Warren Kanyuck ,  Ernest Scott Stickels

IPC分类号： G06G7/00 ,  G06N5/00

CPC分类号： G06K9/00536 ,  G06N3/086

摘要： Genetically adaptive neural network systems and methods provide environmentally adaptable classification algorithms for use, among other things, in multi-static active sonar classification. Classification training occurs in-situ with data acquired at the onset of data collection to improve the classification of sonar energy detections in difficult littoral environments. Accordingly, in-situ training sets are developed while the training process is supervised and refined. Candidate weights vectors evolve through genetic-based search procedures, and the fitness of candidate weight vectors is evaluated. Feature vectors of interest may be classified using multiple neural networks and statistical averaging techniques to provide accurate and reliable signal classification.

摘要翻译： 遗传自适应神经网络系统和方法提供了环境适应性分类算法，其中包括多静态主动声纳分类。 在数据采集开始时采集数据进行分类训练，以改善难以沿岸的环境中声纳能量检测的分类。 因此，在培训过程受到监督和完善的同时开发了现场培训。 候选权重矢量通过基于遗传的搜索过程进化，评估候选权重向量的适应度。 感兴趣的特征向量可以使用多个神经网络和统计平均技术进行分类，以提供准确可靠的信号分类。