Description: 这个软件支持Bayesian衰退和分类模形，它基于神经系统网络和Gaussian作用。它也包括一些根本的程序实现有限和无限混合的模型。-software support this recession and Bayesian classification pattern, It is based on neural network and Gaussian role. It also includes some of the procedures to achieve limited and unlimited mixed model. Platform: |
Size: 1181429 |
Author:方正 |
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Description: 模式识别分类程序，贝叶斯，神经网络分类训练程序，很不错啊-the classification procedures, Bayesian neural network classifier training procedures, and it is very responds : Platform: |
Size: 591571 |
Author:杨宁 |
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Description: 这个软件支持Bayesian衰退和分类模形，它基于神经系统网络和Gaussian作用。它也包括一些根本的程序实现有限和无限混合的模型。-software support this recession and Bayesian classification pattern, It is based on neural network and Gaussian role. It also includes some of the procedures to achieve limited and unlimited mixed model. Platform: |
Size: 1180672 |
Author:方正 |
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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: 模式识别分类程序，贝叶斯，神经网络分类训练程序，很不错啊-the classification procedures, Bayesian neural network classifier training procedures, and it is very responds : Platform: |
Size: 3755008 |
Author:杨宁 |
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Description: 一些数据挖掘算法相关,包含定义网络拓扑,有关高血压研究方面的数据,朴素贝叶斯分类,关联规则基本概念,数据挖掘算法,
决策树方法在数据挖掘中的应用,训练贝叶斯信念网络,后向传播,贝叶斯信念网络,后向传播和可解释性,多层前馈神经网络-Some relevant data mining algorithms, including the definition of network topology, the high blood pressure research data, Naive Bayesian Classifier, the basic concepts of association rules, data mining algorithms, decision tree method in data mining applications, training Bayesian belief networks, to the spread of Bayesian belief networks, to the dissemination and interpretability, multi-layer feedforward neural network Platform: |
Size: 184320 |
Author:fast man |
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Description: Visual C++数字图像模式识别技术及工程实践(随书光盘）人民邮电出版社2003张宏林本书介绍了模式识别和人工智能中的一些基本理论以及一些相关的模型,包括贝叶斯决策、线性判别函数、神经网络理论、隐马尔可夫模型、聚类技术等,同时结合模式识别中的一些经典问题,从多种不同的角度介绍了这些问题的解决思路。-Visual C++ Digital Image Pattern Recognition Technology and Engineering Practice (Book with CD-ROM)张宏林Posts & Telecom Press, 2003 book of pattern recognition and artificial intelligence, introduced some of the basic theory and some related models, including Bayesian decision-making, Linear Discriminant function, neural network theory, hidden Markov models, clustering technologies, combined with some of the classic pattern recognition problems, from the perspective of a variety of introduced ideas to solve these problems. Platform: |
Size: 39604224 |
Author:swallow |
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Description: 从ML-EM 重建算法入手，分析了贝叶斯模型的一些关键点，针对采用传统方法求解MAP问题的局限性，提出一种用于正电子成像的贝叶斯神经网络重建算法，为了保留边缘信息，引入了二进制的保边缘变量，并应用共轭神经网络求解，模拟的重建结果表明，应用这种算法可以得到比ML-EM 算法更好的重建图像@-From the ML-EM reconstruction algorithm start with an analysis of Bayesian model some of the key points, the use of traditional methods for solving the problem of the limitations of MAP, a positron imaging for the Bayesian neural network algorithm, in order to to retain the edge information, the introduction of binary variables edge security, and application of neural network for solving the conjugate, the reconstruction of simulated results show that the algorithm can be more than ML-EM image reconstruction algorithm better @ Platform: |
Size: 285696 |
Author:李浩 |
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Description: 《精通VisualC++数字图像处理模式识别技术及工程实践》介绍了模式识别和人工智能中的一些基本理论，以及一些相关的模型，包括贝叶斯决策、线性判别函数、神经网络理论、隐马尔可夫模型、聚类技术等，同时结合模式识别中的一些问题，比如字符识别、笔迹鉴定、人脸检测、车牌识别、印章识别以及遥感图片、医学图片处理等内容，从多种角度，介绍了解决这些问题的思路-" Proficient in VisualC++ digital image processing, pattern recognition technology and engineering practice," describes the pattern recognition and artificial intelligence in some of the basic theory, and a number of related models, including Bayesian decision-making, linear discriminant function, neural network theory, hidden Markov Cardiff model, clustering technologies, combined with pattern recognition in a number of issues, such as character recognition, handwriting identification, face detection, license plate recognition, seals, and remote-sensing image recognition, medical image processing and other content, from several angles, introduced ideas to solve these problems Platform: |
Size: 11152384 |
Author:吴晶 |
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Description: Major features
BNT supports many types of conditional probability distributions (nodes), and it is easy to add more.
Tabular (multinomial)
Gaussian
Softmax (logistic/ sigmoid)
Multi-layer perceptron (neural network)
Noisy-or
Deterministic
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Size: 12275013 |
Author:SunStacy |
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Description: Bayesian 神经网络，可用于模型构建中变量的筛选-Bayesian neural network，could be applied for variable selection in model construction Platform: |
Size: 2304000 |
Author:cuiyan |
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Description: Prediction of _ Lou Peng bearing network performance of Bayesian neural network based on IP
Platform: |
Size: 2081792 |
Author:fdsfdsf |
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Search - Bayesian neural network