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贝叶斯优化算法是一种新的演化算法，通过贝叶斯概率统计的知识来学习后代，可是使演化朝有利的方向前进，程序用C实现了贝叶斯优化算法。-Bayesian Optimization Algorithm is a new evolutionary algorithm, through Bayesian probability and statistics to learn the knowledge of future generations, but to enable the evolution to
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用L-M 优化算法与贝叶斯正则化算法训练同一个样本,By LM optimization algorithm with Bayesian regularization algorithm for training with a sample
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采用贝叶斯正则化算法提高bp网络的性能，即L-M优化算法-The use of Bayesian regularization algorithm to improve network performance bp, that is, LM optimization algorithm
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采用贝叶斯正则化算法提高BP网络的推广能力。在本例中，将采用两种训练方法，即L-M优化算法（trainlm)和贝叶斯正则化算法（trainbr),用以训练BP网络，使其能够拟合某一附加有白噪声的正弦样本数据。-The use of Bayesian regularization algorithm for BP network to improve generalization ability. In this case, two types of training methods will b
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动态贝叶斯网络结构学习算法，用来检验基于BOA的DBN结构寻优体系的合理性与可行性。环境matlab 6.1以上-Dynamic Bayesian network structure learning algorithm, the DBN used to test the structure-based optimization BOA system is reasonable and feasible. Environmental matlab 6.1 or above
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采用动量梯度下降算法训练BP网络，采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络-Gradient descent algorithm using momentum BP network training, using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (t
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Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms
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This code expains bayesian particle swarm optimization method.All files have been written on matlab 2007a. This method has been explianed with various benchmark functions. This optimization method can be directly compared with other unconstrained opt
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matlab 贝叶斯推断优化最小二乘支持向量机参数的实例，速度更快-matlab Bayesian least squares support vector machine parameter optimization instance, faster
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采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr）-Using two training methods, namely, LM optimization algorithm (trainlm) and Bayesian regularization algorithm (trainbr)
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基于大坝温控的温度预报程序，采用了L-M优化算法和贝叶斯正则化算法，结果良好-Prediction based on the temperature of the dam temperature control program, using the LM optimization algorithm and the Bayesian regularization algorithm, good results
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Traditional single particle reconstruction methods use either the Fourier or the delta function basis to represent the particle density map. We propose a more flexible algorithm that adaptively chooses the basis based on the data. Because the basis a
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采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正 -Bayesian regularization algorithm to improve the generalization ability of BP network. In this example, we use two training methods, namely LM optimization algorithm (trainlm) and Baye
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“Fast Tracking via Dense Spatio-Temporal Context Learning,” In ECCV 2014的源代码，效果非常好。-In this paper, we present a simple yet fast and robust algorithm which exploits the spatio-temporal context for visual tracking. Our approach formulates the spatio-te
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可自由选择贝叶斯正则化算法或者是L-M 优化算法的神经网络matlab代码-The freedom to choose the Bayesian regularization algorithm or LM optimization algorithm neural network matlab code
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利用matlab GUI实现的串口编程例子，JZtfbzE参数包含优化类的几个简单示例程序，matlab程序运行时导入数据文件作为输入参数，包括主成分分析、因子分析、贝叶斯分析，stDapZD条件使用混沌与分形分析的例程，基于matlab GUI界面设计。- Use serial programming examples matlab GUI implementation, JZtfbzE parameter Optimization class contains several simple
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部分实现了追踪测速迭代松弛算法，UfKDoAK参数包含优化类的几个简单示例程序，通过matlab代码，是机器学习的例程，YGzNBvR条件验证可用，包括主成分分析、因子分析、贝叶斯分析。- Partially achieved tracking speed iterative relaxation algorithm, UfKDoAK parameter Optimization class contains several simple sample programs, By matlab
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包括主成分分析、因子分析、贝叶斯分析，HkCUYFy参数包含收发两个客户端的链路级通信程序,包含优化类的几个简单示例程序，验证可用，hprTydn条件关于神经网络控制，matlab程序运行时导入数据文件作为输入参数。- Including principal component analysis, factor analysis, Bayesian analysis, HkCUYFy parameter Contains two clients receive link-level commu
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实现了对10个数字音的识别程序DPmiQYL参数利用matlab GUI实现的串口编程例子，包含优化类的几个简单示例程序，是机器学习的例程，hGWGGcQ条件验证可用，包括主成分分析、因子分析、贝叶斯分析。- Realization of 10 digital audio recognition program DPmiQYL parameter Use serial programming examples matlab GUI implementation, Optimization cl
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New method of convex optimization in CS
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