Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration. Platform: |
Size: 7158 |
Author:姜正茂 |
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Description: DNA分类，包含三中模式识别经典算法的实现：K紧邻，BP神经网络，概率神经网络。-DNA classification, which includes three classic pattern recognition algorithm to achieve : K borders, BP neural networks, probabilistic neural network. Platform: |
Size: 64423 |
Author:郭瑞杰 |
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Description: DNA分类，包含三中模式识别经典算法的实现：K紧邻，BP神经网络，概率神经网络。-DNA classification, which includes three classic pattern recognition algorithm to achieve : K borders, BP neural networks, probabilistic neural network. Platform: |
Size: 192512 |
Author:郭瑞杰 |
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Description: 基于GMM的概率神经网络PNN具有良好的泛化能力，快速的学习能力，易于在线更新,并具有统计学的贝叶斯估计理论基础，已成为一种解决像说话人识别、文字识别、医疗图像识别、卫星云图识别等许多实际困难分类问题的很有效的工具。而且PNN不但具有GMM的大部分优点，还具有许多GMM没有的优点，如强鲁棒性，需要更少的训练语料，可以和其他网络其他理论无缝整合等。-GMM based probabilistic neural network PNN good generalization ability, the ability to learn fast, easy online updates, and with the Bayesian statistical theory based on estimates, and has become a solution as speaker recognition, text recognition, medical image recognition, satellite images and other real recognition when difficulties classification of very effective tool. But GMM PNN is not only the most advantages, but also has many advantages GMM not as strong robustness, require less training corpus, and other networks to other theories, such as seamless integration. Platform: |
Size: 7168 |
Author:姜正茂 |
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Description: 用概率神经网络预测股市的方向变化.对研究神经网络在金融市场上的应用很有帮助。-Using probabilistic neural network prediction of the direction of changes in the stock market. The study of neural networks in the financial market applications helpful. Platform: |
Size: 120832 |
Author:zhbruce |
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Description: very good Gaussian Mixture Models and Probabilistic Decision-Based Neural Networks for Pattern Classification - A Comparative Study document -very good Gaussian Mixture Models and Probabilistic Decision-Based Neural Networks for Pattern Classification- A Comparative Study document Platform: |
Size: 287744 |
Author:B |
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Description: MATLAB神经网络30个案例分析__读者调用案例的时候，只要把案例中的数据换成自己需要处理的数据，即可实现自己想要的网络。该书共有30个MATLAB神经网络的案例(含可运行程序），包括BP、RBF、SVM、SOM、Hopfield、LVQ、Elman、小波等神经网络；还包含PSO(粒子群）、灰色神经网络、模糊网络、概率神经网络、遗传算法优化等内容。-30 case studies of the MATLAB Neural Network __ readers call the case, as long as the data in the case replaced by the data they need to be addressed, you can achieve your desired network. A total of 30 MATLAB neural network case (including running the program) in the book, including BP, RBF, SVM, the SOM, Hopfield, on LVQ, Elman, wavelet neural network also contains the PSO (Particle Swarm), gray neural network, fuzzy networks, probabilistic neural networks, genetic algorithms optimization. Platform: |
Size: 11300864 |
Author:liuwei |
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Description: 自己在各个论坛上搜集的十大算法，Dijkstra算法，Floyd算法，动态规划，分治算法，概率算法，灰色预测，聚类算法，蒙特卡洛，模拟退火算法，神经网络等等，附有算法的原理，部分含有相关的程序源代码。-In various forums to collect the ten algorithms, Dijkstra algorithm, the Floyd algorithm, dynamic programming, divide and conquer algorithms, probabilistic algorithms, gray prediction, clustering algorithms, Monte Carlo, simulated annealing, neural networks, etc., accompanied by the algorithmthe principle, in part contain the source code. Platform: |
Size: 9586688 |
Author:黄绍广 |
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Description: 运用RBPNN径向基概率神经网络的一个源码实实例，通过该源码实例能对RBFNN有个清晰认识
-Radial basis probabilistic neural networks use RBPNN real instance of a source, the source instance have a clear understanding on RBFNN Platform: |
Size: 5120 |
Author:zzhp2010 |
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Description: 本书共有30个MATLAB神经网络的案例,包括BP、RBF、SVM、SOM、Hopfield、LVQ、Elman、小波等神经网络,还包含PSO(粒子群)、灰色神经网络、模糊网络、概率神经网络、遗传算法优化等内容。-The book consists of 30 MATLAB neural network case (including program can be run), including BP, RBF, SVM, SOM, Hopfield, LVQ, Elman, wavelet neural networks, etc. also contains the PSO (PSO), gray neural networks, fuzzy networks, probabilistic neural networks, genetic algorithm optimization and so on. Platform: |
Size: 28765184 |
Author:万二 |
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Description: This submission contains
(1) Journal Article on Zernike Moments, Genetic Algorithm, Feature Selection and Probabilistic Neural Networks.
(2) MATLAB code to do Feature Selection Using Genetic Algorithm.
NB:
(i) This code is short BUT it works incredibly well since we employed GA Toolbox.
(ii) You can run this code directly on your computer since the dataset herein is available in MATLAB software.
(iii) Please do cite my publication to give credit to me (if you use this code).
The citation is as follows:
BABATUNDE Oluleye, ARMSTRONG Leisa J, LENG Jinsong and DIEPEVEEN Dean (2014). Zernike Moments and Genetic Algorithm: Tutorial and Application. British Journal of Mathematics & Computer Science. 4(15):2217-2236.
Or
BABATUNDE, Oluleye and ARMSTRONG, Leisa and LENG, Jinsong and DIEPEVEEN (2014). A Genetic Algorithm-Based Feature Selection. International Journal of Electronics Communication and Computer Engineering: 5(4) 889 905.-This submission contains
(1) Journal Article on Zernike Moments, Genetic Algorithm, Feature Selection and Probabilistic Neural Networks.
(2) MATLAB code to do Feature Selection Using Genetic Algorithm.
NB:
(i) This code is short BUT it works incredibly well since we employed GA Toolbox.
(ii) You can run this code directly on your computer since the dataset herein is available in MATLAB software.
(iii) Please do cite my publication to give credit to me (if you use this code).
The citation is as follows:
BABATUNDE Oluleye, ARMSTRONG Leisa J, LENG Jinsong and DIEPEVEEN Dean (2014). Zernike Moments and Genetic Algorithm: Tutorial and Application. British Journal of Mathematics & Computer Science. 4(15):2217-2236.
Or
BABATUNDE, Oluleye and ARMSTRONG, Leisa and LENG, Jinsong and DIEPEVEEN (2014). A Genetic Algorithm-Based Feature Selection. International Journal of Electronics Communication and Computer Engineering: 5(4) 889 905. Platform: |
Size: 1434624 |
Author:abdalla |
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Search - probabilistic neural networks