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基本遗传算法源程序(基于基本遗传算法的函数最优化C程序)...
基本遗传算法源程序(基于基本遗传算法的函数最优化C程序)-Basic genetic algorithm source code (based on a function of the basic genetic algorithm optimization procedure C)
- 2022-02-15 09:24:04下载
- 积分:1
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基于倒谱特征的带噪语音端点检测.rar格式为vip
基于倒谱特征的带噪语音端点检测.rar格式为vip-based Cepstral Noisy voice endpoint detection. Rar format vip
- 2022-02-01 02:40:37下载
- 积分:1
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神经网络的算法,关于BP网络的编写
神经网络的算法,关于BP网络的编写-neural network algorithm, on the preparation of BP Network
- 2022-12-22 05:05:03下载
- 积分:1
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异步电动机的模糊控制的仿真,大家一起研究.
异步电动机的模糊控制的仿真,大家一起研究.-Fuzzy control induction motor simulation, we study together.
- 2022-06-19 01:13:12下载
- 积分:1
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VC 遗传算法源码
VC 遗传算法源码-VC genetic algorithm source code
- 2022-08-15 11:16:54下载
- 积分:1
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FNN利用MATLAB编程安装nefcon遵循这些步骤:1。打开…
模糊神经网络采用matlab编程 o install NEFCON follow these steps: 1. Unpack the tar file NEFCON.TAR into your MATLAB working directory: tar xf NEFCON.TAR 2. Start MATLAB 3. Change to the installation directory. 4. Change to the NEFCON directory. 5. Start the STARTUP M-file to initialize NEFCON.-FNN using Matlab programming o install NEFCON follow these steps : 1. Unpack the tar file NEFCON.TAR MATLAB into your working directory : tar xf NEFCON.TAR 2. Start MATLAB 3. Change to the installation directory. 4. Change to the NEFCON directory. 5. Start the STARTUP M-file to initialize NEFCON.
- 2023-07-13 05:35:03下载
- 积分:1
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RBF
本文采用红外光电传感器技术, 建立了一个基于神经网络的客流计数系统, 与传
统的仅利用光电传感器计数方法相比, 该方法提高了实时客流计数准确率。为了更好的分
类识别计数, 针对采集的连续的时空序列客流数据特点, 改进了已有的分割方法和针对客
流实际情况的特征提取方法。最后经过稀疏和密集客流模拟仿真测试, 结果表明, 本文所
提出的模型能够识别多人并排的情况, 误差率较低, 具有理论和实际意义。-RBF
- 2022-05-27 06:08:00下载
- 积分:1
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基于MATLAB完成的神经网络源程序
大家
基于MATLAB完成的神经网络源程序
大家-Based on the MATLAB neural network to complete the U.S. source
- 2022-12-09 20:40:03下载
- 积分:1
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我的英国石油网
人工神经网络网上发给我的BP-ANN Internet to my BP
- 2023-03-11 16:10:03下载
- 积分:1
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使用二进制和实数编码变量的遗传算法实现。混合变量…
This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g >= 0) and normalized (see the sample problem in prob1 in objective()).-This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g gt;= 0) and normalized (see the sample problem in prob1 in objective()).
- 2022-02-07 16:02:59下载
- 积分:1