標(biāo)題: Titlebook: Entropy and Information Theory; Robert M. Gray Book 19901st edition Springer-Verlag New York 1990 Normal.Random variable.Shannon.behavior. [打印本頁] 作者: 相似 時(shí)間: 2025-3-21 17:43
書目名稱Entropy and Information Theory影響因子(影響力)
書目名稱Entropy and Information Theory影響因子(影響力)學(xué)科排名
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書目名稱Entropy and Information Theory網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Entropy and Information Theory被引頻次
書目名稱Entropy and Information Theory被引頻次學(xué)科排名
書目名稱Entropy and Information Theory年度引用
書目名稱Entropy and Information Theory年度引用學(xué)科排名
書目名稱Entropy and Information Theory讀者反饋
書目名稱Entropy and Information Theory讀者反饋學(xué)科排名
作者: 可忽略 時(shí)間: 2025-3-21 21:49
Developments in French Politicsf entropy rates are proved and a mean ergodic theorem for relative entropy densities is given. The principal ergodic theorems for relative entropy and information densities in the general case are given in the next chapter.作者: 元音 時(shí)間: 2025-3-22 01:40 作者: 遍及 時(shí)間: 2025-3-22 07:51 作者: REIGN 時(shí)間: 2025-3-22 09:44 作者: 豪華 時(shí)間: 2025-3-22 14:59 作者: 豪華 時(shí)間: 2025-3-22 20:12
https://doi.org/10.1007/978-3-030-04711-5perties of information and entropy rates of finite alphabet processes. We show that codes that produce similar outputs with high probability yield similar rates and that entropy and information rate, like ordinary entropy and information, are reduced by coding. The discussion introduces a basic tool作者: ASSET 時(shí)間: 2025-3-22 23:30 作者: NEX 時(shí)間: 2025-3-23 04:37 作者: GUILE 時(shí)間: 2025-3-23 08:25
Developments in French Politicsf entropy rates are proved and a mean ergodic theorem for relative entropy densities is given. The principal ergodic theorems for relative entropy and information densities in the general case are given in the next chapter.作者: 子女 時(shí)間: 2025-3-23 13:00 作者: 漂泊 時(shí)間: 2025-3-23 17:14
https://doi.org/10.1057/978-1-137-59491-4g., a random variable, vector, or waveform. Hence sequences of pairs of random objects such as {..,..} are included in the general framework. We now focus on the possible interrelations between the two components of such a pair process. In particular, we consider the situation where we begin with on作者: 長(zhǎng)矛 時(shí)間: 2025-3-23 19:58 作者: Presbyopia 時(shí)間: 2025-3-23 22:15
rst and then later form the overall result by combining these special cases. In the first case we assume that the channel is noiseless, but it is constrained in the sense that it can only pass . bits per input symbol to the receiver. Since this is usually insufficient for the receiver to perfectly r作者: frozen-shoulder 時(shí)間: 2025-3-24 02:38 作者: 諷刺 時(shí)間: 2025-3-24 07:11 作者: 有害 時(shí)間: 2025-3-24 11:32 作者: Aggressive 時(shí)間: 2025-3-24 17:42 作者: 抗生素 時(shí)間: 2025-3-24 19:18
https://doi.org/10.1007/978-3-031-67019-0eful, however, to explicitly treat the notion of time as a transformation of sequences produced by the source. Thus in addition to the common random process model we shall also consider modeling sources by dynamical systems as considered in ergodic theory.作者: Magisterial 時(shí)間: 2025-3-25 01:04 作者: 減弱不好 時(shí)間: 2025-3-25 06:21 作者: 憤憤不平 時(shí)間: 2025-3-25 10:23 作者: 類似思想 時(shí)間: 2025-3-25 14:35 作者: 四目在模仿 時(shí)間: 2025-3-25 16:31
Information Rates I, We obtain an ergodic theorem for information densities of finite alphabet processes as a simple application of the general ShannonMcMillan-Breiman theorem coupled with some definitions. In Chapter 6 these results easily provide .. ergodic theorems for information densities for more general processes.作者: Endoscope 時(shí)間: 2025-3-25 21:05
Information Rates II,we apply the results of Chapter 5 on divergence to the definitions of this chapter for limiting information and entropy rates to obtain a number of results describing the behavior of such rates. In Chapter 8 almost everywhere ergodic theorems for relative entropy and information densities are proved.作者: 怕失去錢 時(shí)間: 2025-3-26 01:03
Coding for noisy channels,d channel code. This division is natural in the sense that optimizing a code for a particular source may suggest quite different structure than optimizing it for a channel. The structures must be compatible at some point, however, so that they can be used together.作者: FAZE 時(shí)間: 2025-3-26 07:08
https://doi.org/10.1007/978-3-030-98717-6 processes and that this behavior is a key factor in developing the coding theorems of information theory. We now introduce the various notions of entropy for random variables, vectors, processes, and dynamical systems and we develop many of the fundamental properties of entropy.作者: glacial 時(shí)間: 2025-3-26 08:41 作者: inflate 時(shí)間: 2025-3-26 15:55 作者: resilience 時(shí)間: 2025-3-26 18:40
Relative Entropy,n of these definitions to infinite alphabets will follow from a general definition of divergence. Many of the properties of generalized information measures will then follow from those of generalized divergence.作者: 紡織品 時(shí)間: 2025-3-26 21:23
https://doi.org/10.1007/978-3-030-03380-4gap is left between these asymptotic upper and lower bounds in the limit as . → ∞. They use martingale theory to show that the values between which the limiting density is sandwiched are arbitrarily close to each other, but we shall see that this is not necessary and this property follows from the results of Chapter 6.作者: 幸福愉悅感 時(shí)間: 2025-3-27 01:18 作者: 女歌星 時(shí)間: 2025-3-27 07:36 作者: organism 時(shí)間: 2025-3-27 11:05
Channels and Codes,pair process {..,..} will inherit stationarity and ergodic properties from the original source {..}. We will also be interested in the behavior resulting when the output of one channel serves as the input to another, that is, when we form a new channel as a cascade of other channels. Such cascades y作者: 使糾纏 時(shí)間: 2025-3-27 14:23 作者: 血友病 時(shí)間: 2025-3-27 21:31 作者: DIS 時(shí)間: 2025-3-28 00:03
Raptor Mortality in Urban Landscapesotically dominated by a stationary measure and hence to all AMS processes. The generalizations to AMS processes build on the Billingsley theorem for the stationary mean. Following generalizations of the definitions of entropy and information, corresponding generalizations of the entropy ergodic theo作者: FLAIL 時(shí)間: 2025-3-28 05:37 作者: 杠桿 時(shí)間: 2025-3-28 09:36 作者: 壓碎 時(shí)間: 2025-3-28 12:26 作者: 聲明 時(shí)間: 2025-3-28 18:17 作者: painkillers 時(shí)間: 2025-3-28 19:12
Entropy and Information,dern age of ergodic theory. We shall see that entropy and related information measures provide useful descriptions of the long term behavior of random processes and that this behavior is a key factor in developing the coding theorems of information theory. We now introduce the various notions of ent作者: Omnipotent 時(shí)間: 2025-3-28 23:51
The Entropy Ergodic Theorem,odic theorem of information theory or the asymptotic equipartion theorem, but it is best known as the Shannon-McMillan-Breiman theorem. It provides a common foundation to many of the results of both ergodic theory and information theory. Shannon [129] first developed the result for convergence in pr作者: Neonatal 時(shí)間: 2025-3-29 04:29
Information Rates I,perties of information and entropy rates of finite alphabet processes. We show that codes that produce similar outputs with high probability yield similar rates and that entropy and information rate, like ordinary entropy and information, are reduced by coding. The discussion introduces a basic tool作者: Allure 時(shí)間: 2025-3-29 07:20 作者: HAUNT 時(shí)間: 2025-3-29 13:53 作者: 的’ 時(shí)間: 2025-3-29 17:16
Relative Entropy Rates,f entropy rates are proved and a mean ergodic theorem for relative entropy densities is given. The principal ergodic theorems for relative entropy and information densities in the general case are given in the next chapter.作者: remission 時(shí)間: 2025-3-29 21:55 作者: 排出 時(shí)間: 2025-3-30 03:31 作者: 約會(huì) 時(shí)間: 2025-3-30 06:20
