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Least squares twin support vector machines for pattern classification
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人脸的研究是跨越人文科学与自然科学的新兴交叉研究领域,在最近几年得到了模式识别领域众多学者的重视,也取得了良好的研究成果。针对人脸这种生物特征的识别,在其过程中最为重要的一个环节是特征的提取,更好的提取出人脸的特征,将会使得识别更有有效和准确,提高分类的同时,也是的识别率有良好的提高。-Face recognition research is a new cross field across the humanities and natural science, had many scholar
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有详细的注释,解耦,恢复原信号,可以实现模式识别领域的数据的分类及回归。- There are detailed notes, Decoupling, restore the original signal, You can achieve data classification and regression pattern recognition.
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仿真效果非常好,可以实现模式识别领域的数据的分类及回归,用MATLAB编写的遗传算法路径规划。- Simulation of the effect is very good, You can achieve data classification and regression pattern recognition, Genetic algorithms using MATLAB path planning.
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包括最后计算压缩图像的峰值信噪比和压缩效果的源码,可以实现模式识别领域的数据的分类及回归,pwm整流器的建模仿真。- Including the final calculation of the compressed image peak signal to noise ratio and compression of the source, You can achieve data classification and regression pattern recognition, Model
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计算时间和二维直方图,比较了软阈值,硬阈值及当今各种阈值计算方法,可以实现模式识别领域的数据的分类及回归。- Computing time and two-dimensional histogram, Comparison of soft threshold and hard threshold and today various threshold calculation method, You can achieve data classification and regression pa
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