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In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. With the weights of the trained neural networks there are created kernel window
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A Hybrid GMM-SVM System for text independent speaker Recognition Sytem
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针对传统的ＢＰ或ＧＡ对模糊神经网络的识别应用存在收敛容易陷入局部极小 识别率低下等问题 提出一
种基于ＢＦＧＳ的混合遗传算法 其基本思想为 首先构造一种前馈型模糊神经网络结构 然后用遗传算法进化若干代
后 当目标函数的梯度或者范数小于预先设定值 则改用ＢＦＧＳ算法进行优化识别 仿真实验表明 对比ＧＡ该算法
收敛速度较快 识别精度提高了约７％ 能够较好地应用于一类模糊神经网络的识别-In traditional BP or GA to identify the application
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它是混合核函数方面的，对于分类的研究有很好的帮助的作用。而且是关于人脸识别的。-It is a hybrid kernel function aspects of the study of the role of classification good help. And about face recognition.
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Speech Recognition with Support Vector Machines in a Hybrid Syste
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A Hybrid SVM/HMM Acoustic Modeling Approach to Automatic Speech Recognition
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