現代數字與模擬通信係統(第4版)(英文版) [Modern Digital and Analog Communication Systems,International Fourth Edition] pdf epub mobi txt 電子書 下載
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關於最新技術進步和應用的討論。新增瞭介紹擴頻通信、頻率選擇性信道和OFDM係統的章節(第11章和第12章)。新增的和更新過的可供學生實踐的MATLAB實例。靈活的組織形式(參見《現代數字與模擬通信係統(第4版)(英文版)》前言)容納瞭各種課程框架,包括一學期、兩個學期、一季度及兩個季度。盡可能給齣直觀的講解(而不僅僅是證明),進而啓發式地解釋理論成果。包含CDMA、OFDM.均衡、軟解碼、Turbo碼、LDPC等新內容。
內容簡介
《現代數字與模擬通信係統(第4版)(英文版)》是電子工程領域中的理想的通信係統入門教材。作者首先介紹瞭信號與係統的基礎理論和通信的核心問題,然後給齣瞭設計和分析數字通信係統的工具。內容涵蓋基本的通信理論、必要的數學基礎及擴頻通信等現代通信技術。啓發性的講解方法、精心挑選的例題和更新的MATLAB練習使本書成為易於被學生理解和接受的通信係統理論與應用的入門教材。
《現代數字與模擬通信係統(第4版)(英文版)》作者長期從事相關領域的科研和教學工作,書中係統介紹從調製解調等通信基本理論到OFDM等現代通信技術的內容,包含概率論和隨機過程的基本知識,增加瞭CDMA.OFDM.均衡、軟解碼、Turbo碼和LDPC等近年來通信技術領域的熱點技術,並包含大量現實生活中的實例。
作者簡介
B·P·拉茲,美國加利福尼亞大學薩剋拉門托分校電機與電子工程係名譽教授,IEEE會士。
丁峙,美國加利福尼亞大學戴維斯分校電氣與計算機工程係教授,IEEE會士。IEEE電路與係統協會2004~2005年度傑齣講師,IEEE通信協會2008~2009年度傑齣講師。
內頁插圖
目錄
第1章 簡介
第2章 信號與信號空間
第3章 信號的分析和傳輸
第4章 幅度調製與解調
第5章 角度調製與解調
第6章 采樣和模數轉換
第7章 數字傳輸原理
第8章 概率論基礎
第9章 隨機過程和譜分析
第10章 數字通信係統的性能分析
第11章 擴頻通信
第12章 綫性信道失真下的數字通信
第13章 信息論介紹
第14章 糾錯編碼
第15章 糾錯編碼
附錄A 一些信號集的正交性
附錄B 柯西-施瓦茨不等式
附錄C 矢量集的格拉姆-施密特正交化
附錄D 矩陣的基本性質和運算
附錄E 其他
精彩書摘
As noted earlier, channel noise is a major factor limiting communication performance because it is random and cannot be removed by prediction. On other other hand, randomness isalso closely associated with the desired signals in communications. Indeed, randomness is theessence of communication. Randomness means unpredictabiliry, or uncertainty, of a source message. If a source had no unpredictability, like a friend who always wants to repeat the samestory on "how I was abducted by an alien," then the information would be known before handand would contain no information. Similarly, if a person winks, it conveys some informationin a given context. But if a person winks continuously with the regularity of a clock, the winks convey no information. In short, a predictable signal is not random and is fully redundant.Thus, a message contains information only if it is unpredictable. Higher predictability meanshigher redundancy and, consequently, less information. Conversely, more unpredictable or lesslikely random signals contain more information.
Source coding reduces redundancy based on the predictability of the message source. The objective of source coding is to use codes that are as short as possible to represent the sourcesignal. Shorter codes are more efficient because they require less time to transmit at a givendata rate. Hence, source coding should remove signal redundancy while encoding and transmitting the unpredictable, random part of the signal. The more predictable messages contain more redundancy and require shorter codes, while messages that are less likely contain more information and should be encoded with longer codes. By assigning more likely messages withshorter source codes and less likely messages with longer source codes, one obtains more efficient source coding. Consider the Morse code, for example.ln this code, various combinations of dashes and dots (code words) are assigned to each letter. To minimize transmission time,shorter code words are assigned to more frequently occurring(more probable) letters (suchas e,t, and a) and longer code words are assigned to rarely occurring (less probable) letters(such as x, q, and z). Thus, on average, messages in English would tend to follow a knownletter distribution, thereby leading to shorter code sequences that can be quickly transmitted.This explains why Morse code is a good source code.
It will be shown in Chapter 13 that for digital signals, the overall transmission time is minimized if a message(or symbol) of probability P is assigned a code word with a lengthproportional to log (1/P). Hence, from an engineering point of view, the information of amessage with probability P is proportional to log (1/P). This is known as entropy (source)coding.
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前言/序言
現代數字與模擬通信係統(第4版)(英文版) [Modern Digital and Analog Communication Systems,International Fourth Edition] 下載 mobi epub pdf txt 電子書
現代數字與模擬通信係統(第4版)(英文版) [Modern Digital and Analog Communication Systems,International Fourth Edition] pdf epub mobi txt 電子書 下載