標(biāo)題: Titlebook: An Information-Theoretic Approach to Neural Computing; Gustavo Deco,Dragan Obradovic Book 1996 Springer-Verlag New York, Inc. 1996 calculu [打印本頁] 作者: 人工合成 時間: 2025-3-21 17:22
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書目名稱An Information-Theoretic Approach to Neural Computing讀者反饋
書目名稱An Information-Theoretic Approach to Neural Computing讀者反饋學(xué)科排名
作者: Confess 時間: 2025-3-21 23:56
https://doi.org/10.1007/978-3-642-92788-1asily applied are stochastic Boolean networks, i.e. Boltzmann Machines, which are the main topic of this chapter. The simplicity is due to the fact that the outputs of the network units are binary (and therefore very limited) and that the output probabilities can be explicitly calculated.作者: FLAIL 時間: 2025-3-22 02:31
Die Prognose der Essentiellen Hypertoniering learning or by appropriately modifying the cost function. Akaike’s and Rissanen’s methods for formulating cost functions which naturally include model complexity terms are presented in Chapter 7 while the problem of generalization over an infinite ensemble of networks is presented in Chapter 8.作者: 冒號 時間: 2025-3-22 06:30
Nonlinear Feature Extraction: Boolean Stochastic Networksasily applied are stochastic Boolean networks, i.e. Boltzmann Machines, which are the main topic of this chapter. The simplicity is due to the fact that the outputs of the network units are binary (and therefore very limited) and that the output probabilities can be explicitly calculated.作者: 機制 時間: 2025-3-22 12:35
Information Theory Based Regularizing Methodsring learning or by appropriately modifying the cost function. Akaike’s and Rissanen’s methods for formulating cost functions which naturally include model complexity terms are presented in Chapter 7 while the problem of generalization over an infinite ensemble of networks is presented in Chapter 8.作者: 權(quán)宜之計 時間: 2025-3-22 16:44
Book 1996rks, but all the relevant concepts from information theory are carefully introduced and explained. Consequently, readers from several different scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this to be a very valuable introduction to this topic.作者: 小故事 時間: 2025-3-22 20:50
Book 1996mulation of neural networks from the information-theoretic viewpoint. They show how this perspective provides new insights into the design theory of neural networks. In particular they show how these methods may be applied to the topics of supervised and unsupervised learning including feature extra作者: CHOKE 時間: 2025-3-22 22:52
Linear Feature Extraction: Infomax Principleenables processing of the higher order cognitive functions. Chapter 3 and Chapter 4 focus on the case of linear feature extraction. Linear feature extraction removes redundancy from the data in a linear fashion.作者: 制造 時間: 2025-3-23 04:20
Konstitutioneller h?molytischer IkterusThis chapter presents a brief overview of the principal concepts and fundaments of information theory and the theory of neural networks.作者: Wernickes-area 時間: 2025-3-23 09:07 作者: 過濾 時間: 2025-3-23 13:22
Die Prognose der Essentiellen HypertonieThe statistical theory of infinite ensemble of networks with fixed parameters was discussed in the previous chapter. The posteriori distribution on the ensemble was determined by maximizing the ensemble entropy. Consequently, the learning in such an ensemble model was reduced to determination of the best temperature.作者: Wallow 時間: 2025-3-23 13:53 作者: 受人支配 時間: 2025-3-23 20:25
Independent Component Analysis: General Formulation and Linear CaseThis chapter formulates the problem of . (ICA) as a search for an information-preserving linear mapping which results in statistically independent output components. The mathematical tools used herein originate from information theory and statistical analysis.作者: entreat 時間: 2025-3-24 02:08 作者: 外向者 時間: 2025-3-24 03:59
An Information-Theoretic Approach to Neural Computing978-1-4612-4016-7Series ISSN 1431-6854 作者: 樂章 時間: 2025-3-24 08:21 作者: probate 時間: 2025-3-24 14:27
Perspectives in Neural Computinghttp://image.papertrans.cn/a/image/155053.jpg作者: Introduction 時間: 2025-3-24 17:44
https://doi.org/10.1007/978-1-4612-4016-7calculus; complex system; control; information theory; learning; neural networks; supervised learning作者: MUT 時間: 2025-3-24 20:37 作者: ethereal 時間: 2025-3-25 02:54
G. Bi?rck,G. Blomqvist,J. Sieversfor modeling and control of nonlinear and complex systems. The ability of neural networks to extract dependencies from measured data and complement the existing analytic knowledge of the underlying phenomena makes them a valuable tool in addressing a wide range of applications. The interaction betwe作者: Fraudulent 時間: 2025-3-25 03:52 作者: 好開玩笑 時間: 2025-3-25 11:14 作者: 一個攪動不安 時間: 2025-3-25 13:59 作者: 大洪水 時間: 2025-3-25 16:00 作者: 莊嚴(yán) 時間: 2025-3-25 22:26
https://doi.org/10.1007/978-3-662-41465-1l physics [8.4–8.7]. In the statistical physics approach an ensemble of neural networks is used to address the problem of generalization of learning from a finite number of noisy training examples. The ensemble treatment of neural networks [8.4–8.7] assumes that the final model is a probabilistic mo作者: 眉毛 時間: 2025-3-26 03:03
Die Prognose der Essentiellen Hypertonieuirement has to be built into the training mechanism either by constantly monitoring the behavior of the trained network on an independent data set during learning or by appropriately modifying the cost function. Akaike’s and Rissanen’s methods for formulating cost functions which naturally include 作者: 歡騰 時間: 2025-3-26 08:13 作者: subacute 時間: 2025-3-26 11:45
Linear Feature Extraction: Infomax Principleenables processing of the higher order cognitive functions. Chapter 3 and Chapter 4 focus on the case of linear feature extraction. Linear feature extraction removes redundancy from the data in a linear fashion.作者: congenial 時間: 2025-3-26 14:28 作者: 創(chuàng)造性 時間: 2025-3-26 20:52 作者: BRUNT 時間: 2025-3-26 22:57 作者: 現(xiàn)任者 時間: 2025-3-27 05:04 作者: rectum 時間: 2025-3-27 08:58
Information Theory Based Regularizing Methodsuirement has to be built into the training mechanism either by constantly monitoring the behavior of the trained network on an independent data set during learning or by appropriately modifying the cost function. Akaike’s and Rissanen’s methods for formulating cost functions which naturally include 作者: Enthralling 時間: 2025-3-27 10:10
Introduction in treating from an application point of view different, but methodologically strikingly similar problems. Consequently, neural networks stimulated advances in modern optimization, control, and statistical theories. On the other hand, information theoretic quantities like entropy, relative entropy 作者: 你正派 時間: 2025-3-27 13:47 作者: 箴言 時間: 2025-3-27 21:40
Supervised Learning and Statistical Estimationunknown process parameters. Although there is a significant conceptual difference between the two mentioned assumptions, there are many instances where they lead to the identical results. In this book we focus our attention on the statistical estimation of the process parameters.作者: 情愛 時間: 2025-3-28 00:10
Statistical Physics Theory of Supervised Learning and Generalization the ensemble volume where the initial volume was fixed by the . distribution [8.4–8.5]. A principle similar to the principle of minimum predictive description length [8.9–8.11] is derived in this framework by applying the maximum likelihood approach to the problem of explaining the data by the ense作者: MILL 時間: 2025-3-28 04:16 作者: 膝蓋 時間: 2025-3-28 07:16
1431-6854 ent scientific disciplines, notably cognitive scientists, engineers, physicists, statisticians, and computer scientists, will find this to be a very valuable introduction to this topic.978-1-4612-8469-7978-1-4612-4016-7Series ISSN 1431-6854 作者: Dappled 時間: 2025-3-28 12:34
G. Bi?rck,G. Blomqvist,J. Sievers in treating from an application point of view different, but methodologically strikingly similar problems. Consequently, neural networks stimulated advances in modern optimization, control, and statistical theories. On the other hand, information theoretic quantities like entropy, relative entropy 作者: GONG 時間: 2025-3-28 16:27 作者: Externalize 時間: 2025-3-28 22:40
Die Prognose der Essentiellen Hypertonieunknown process parameters. Although there is a significant conceptual difference between the two mentioned assumptions, there are many instances where they lead to the identical results. In this book we focus our attention on the statistical estimation of the process parameters.作者: rectum 時間: 2025-3-29 01:06
https://doi.org/10.1007/978-3-662-41465-1 the ensemble volume where the initial volume was fixed by the . distribution [8.4–8.5]. A principle similar to the principle of minimum predictive description length [8.9–8.11] is derived in this framework by applying the maximum likelihood approach to the problem of explaining the data by the ense作者: 武器 時間: 2025-3-29 03:39
10樓作者: 陰險 時間: 2025-3-29 09:35
10樓作者: Notorious 時間: 2025-3-29 13:02
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