【摘 要】
：
随着VLSI技术的迅猛发展,对神经网络与隐马尔柯夫模型(HMM’s)之问的关系研究已成为信息处理领域的一个重要的研究方向.在分析高阶神经网络和二阶HMM’s的结构及算法的基础上
【机 构】
：
华中理工大学电子与信息工程系,华中理工大学电子与信息工程系,华中理工大学电子与信息工程系
论文部分内容阅读
随着VLSI技术的迅猛发展,对神经网络与隐马尔柯夫模型(HMM’s)之问的关系研究已成为信息处理领域的一个重要的研究方向.在分析高阶神经网络和二阶HMM’s的结构及算法的基础上,提出了这两种模型的统一数学模型,从而为这两种模型的systolic设计奠定了基础.
With the rapid development of VLSI technology, the research on the relationship between neural networks and Hidden Markov Models (HMM’s) has become an important research area in the field of information processing.After analyzing the structure of higher order neural networks and second-order HMM’s, Based on the algorithm, a unified mathematical model of these two models is proposed, which lays the foundation for the systolic design of these two models.
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