通信与电子信息科技英语教学课件汇总完整版电子教案全书课件(最新)

1、 New words and phrases outcome n.结果，结局 statistics n.统计，统计数字（信息） statistic adj.统计上的；n.统计量 statistical adj.统计的,统计学的 toss v.投,掷 die n.骰子(pl.dice) dice n.骰子;vi.掷骰子 intuitive adj.直觉的;直观的 intuitively adv.直觉地；直观地 analogously adv.类似地,类比地 conceptually adv.概念地 Random ProcessesRandom Processessimultaneous adj.

2、同时的,同时发生的collection n.集合,集 dentical adj.同一的,同样的 individual adj.个别的,单独的 ensemble n.集,总体 ensemble average 集平均variable n.变量;变元 random variable 随机变量 stationary adj.平稳的ergodic adj.各态历经的,遍历的 ergodic process 各态历经过程，遍历过程Random Processesdeterministic adj.确定性的normalize vt.使标准化,使规格化normalized adj.规格化的，归一化的expe

3、ctation n.期望(值)product n.乘积truncate vt.截短；截断periodic adj.周期的covariance n.协方差uncorrelated adj.不相关的uniform adj.均匀的，一致的overlap v.(部分)重叠separation n.间隔，距离spacing n.间隔，间距random process 随机过程on the average 平均, 按平均数计算; 一般地说Random Processesmake measurement 量度sample function 样本函数statistical average 统计平均(值)pro

4、bability density function 概率密度函数statistical characteristic 统计特性autocorrelation function 自相关函数in connection with 关于，与有关 physical significance 物理意义Fourier transform 傅里叶变换power spectral density 功率谱密度be at liberty to(do) 被允许; 可随意gaussian process 高斯过程physical fact 外界存在的事实upperfrequency limit 频率上限Random P

5、rocessesfall off 下降, 减少in the limit 在极限情况下delta function 函数，狄拉克函数random pulse 随机（杂乱）脉冲time invariant 时不变的Parsevals theorem 巴塞瓦尔定理statistically independent 统计独立successive pulse 连续脉冲be representative of 表示，代表，代表的特征Random Processes To determine the probabilities of the various possible outcomes of an e

6、xperiment,it is necessary to repeat the experiment many times. Suppose then that we are interested in establishing the statistics associated with the tossing of a die. We might proceed in either of two ways. On one hand, we might use a single die and toss it repeatedly. Alternatively, we might toss

7、simultaneously a very large number of dice. Intuitively, we would expect that both methods would give the same results. Thus, we would expect that a single die would yield a particular outcome, on the average, of 1 time out of 6.Similarly, with many dice we would expect that 1/6 of the dice tossed w

8、ould yield a particular outcome. Analogously, let us consider a random process such as a noise waveform n(t).To determine the statistics of the noise, we might make repeated measurements of the noise voltage output of a single noise Random Processessource, or we might, at least conceptually,make sim

9、ultaneous measurements of the output of a very large collection of statistically identical noise sources. Such a collection of sources is called an ensemble, and the individual noise waveforms are called sample functions. A statistical average may be determined from measurements made at some fixed t

10、imet=t1 on all the sample functions of the ensemble. Thus to determine, say, n2(t), we would, at t=t1, measure the voltages n(t1) of each noise source, square and add the voltages, and divide by the (large) number of sources in the ensemble. The average so determined is the ensemble average of n2(t1

11、). Now n(t1)1is a random variable and will have associated with it a probability density function. The ensemble averages will be identical with the statistical averages and may be represented by the same symbols. Thus the statistical or ensemble average of n2(t1) maybe written Random ProcessesEn2(t1

12、)=n2(t1). The averages determined by measurements on a single sample function at successive times will yield a time average, which we represent asn2(t).Exercises. Please translate the following words and phrases into Chinese. 1. sample function2. ensemble average 3. physical significance4. a Fourier

13、 transform pair5. deterministic waveform6. in the limit 7. time invariant8. an upperfrequency limit9. Parsevals theorem 10. random pulses样本函数总体均值物理意义傅立叶变换对确定性波型在极限情况下时不变的频率上限巴塞瓦尔定理随机脉冲Exercises. Please translate the following words and phrases into English.1. 随机过程2. 统计平均3. 随机变量4. 自相关函数5. 傅里叶变换6. 功率谱

14、密度7. 概率密度函数8. 高斯过程9. 平稳过程10. 统计独立random process statistical average random variable autocorrelation function Fourier transform power spectral density probability density function gaussian process a stationary process statistically independent 11. 时间平均(值)12. 统计特性13. 各态历经过程14. 狄拉克函数time average statis

15、tical characteristic ergodic process delta function Exercises. Fill in the blanks with the missing word(s). 1. The ensemble averages will be identical the statistical averages and may be represented by the same symbols.2. The averages determined by measurements a single sample Function successive ti

16、mes will yield a time average, which we represent as n2(t1).3. Suppose, for example, that the statistical characteristics of the sample Functions the ensemble were changing with time.4. For it may happen that while each sample function is stationary the individual sample functions may differ statist

17、ically one another.5. As an extension of that result we shall define the power spectral density of a random process the same way.withonatinfrominExercises6. It is interest to inquire whether G(f) defined Eq. (1.2) for a random process has a physical significance whichcorresponds to the physical sign

18、ificance of G(f) for deterministic waveforms.8. Hence, if we should select some sample function, a knowledge of the value of n(t) at time t would be no assistance improving our ability to predict the value attained by that same sample function at time t+.9. Hence,whenever we make an observation or m

19、easurement of the pulse waveform which extends a duration long enough so that the average observed pulse shape,such as their amplitudes,widths,and spacings are representative of the waveform generally,we shall find that Eq.(1.12)applies.ofinofinoverExercises10. Let us select a section of this wavefo

20、rm which extends -T/2 -T/2.11. Since we have assumed an ergodic process,we are at liberty to (perform, performing) the averaging any sample function of the ensemble, since every sample function will yield the same result.tofromperformoverExercises. Answer the following questions according to the tex

21、t.1.Please describe the relationship between the ergodic process and the stationary process.2. What are random pulses?3. What is the relationship between the power spectral density G(f) and the autocorrelation function R( ).4. What is referred to as ergodic?An ergodic process is stationary, but a st

22、ationary process is not necessarily ergodic.The random pulses are of the same form but have random amplitudes and statistically independent random times of occurrenceThe power spectral density and the autocorrelation function constitute a Fourier transform pair. When the nature of a random process i

23、s such that ensemble and time averages are identical, the process is referred to as ergodic.Exercises5. What is white noise? Why do we call it “white”?White noise has a power spectral density which is uniform over all frequencies. Such noise is referred to as “white” noise in analogy with the consid

24、eration that white light is a combination of all colors, that is, colors of all frequencies多媒体通信技术 孙学康Channel CapacityNew words and phrases 1abstraction n.抽象；抽象观念2encompass vt. 包括，包含3devise vt.设计, 发明4whereby adv.凭那个；由此5arbitrarily adv. 任意地6theorem n. 定理7infrequent adj. 很少发生的, 罕见的8override vt. 压倒, 制服

25、，凌驾9thereby adv. 由此,因此,从而10gaussian adj. 高斯的 Gauss高斯(17771855, 德国数学家、天文学家) 11unity n.一，单一12complementary adj.补充的；互补的Channel Capacity13derivation n.推导, 导出，公式推导14formidable adj.困难的，棘手的,可怕的15undertake vt.进行, 从事16presumed adj. 假定的, 推测的 presumably adv.推测起来,大概,估计,可能17likelihood n.可能, 可能性likely adj. 可能，可能的

26、18interval n.间隔，时间间隔19rounding n.舍入(成整数); 四舍五入20abrupt adj.不连续的，突然的，急剧的，陡的21reliably adv.可靠地，安全地，确实地22heuristic adj.启发式的, 渐进的23intuitive adj.直觉的; 直观的 intuitively adv.直觉地, 直观地24contemplate vt.预期(料)Channel Capacity25vice versa adv.反之亦然（viceversa) 26quantize vt.量化27reception n.接收28extreme adj.极端的，极度的,

27、偏激的29attenuate vt.衰减，使衰减30distort vt.失真，使失真distortion n.失真,畸变31equalizer n.均衡器32recoverable adj.可恢复的1 enter into 参加，成为一部分，涉及2 due to 由于; 起因于; 归功于3 be something of 有一点4 in principle 原则上, 大致上on principle 按照原则（或道德标准）Channel Capacity5 provided that 假如, 设若6 probability of error(error probability) 误码率，误差概

28、率 7 be close to 接近, 靠近8 bandlimited gaussian channel 限带高斯信道9 physical system 物理系统,实际系统10 turn out （常与to, that连用）结果，结果是11 lower bound 下界, 下限12 upper limit 上限13 rootmeansquare 均方根，均方根值；均方根(的) rootmeansquare error 均方根(有效值)误差14 amount of information （information content; quantity of information; informa

29、tion quantity）信息量15 ideal lowpass filter 理想低通滤波器Channel Capacity16 rise time 上升时间17 as a matter of convenience 为方便起见18 white Gaussian noise(white gaussian noise) 高斯白噪声 19 on the other hand 另一方面20 trade off 交替换位，折衷选择(tradeoffn.折衷，权衡)21 signaltonoise ratio 信号噪声比，信噪比（SNR,S/N）22 be free to 随意,任意,不受拘束23

30、make up for 补偿Channel Capacity The importance of the concept of information rate is that it enters into a theorem due to Shannon which is fundamental to the theory of communications. This theorem is concerned with the rate of transmission of information over a communication channel. While we have us

31、ed the term communication channel on many occasions，it is well to emphasize at this point, that the term, which is something of an abstraction, is intended to encompass all the features and component parts of the transmission system which introduce noise or limit the bandwidth. . Shannons Theorem, C

32、hannel Capacity Shannons theorem says that it is possible, in principle, to devise a means whereby a communications system will transmit information with an arbitrarily small probability of error provided that the information rate R is less than or equal to a rate C called the channel capacity.To pu

33、t the matter more formally, we have the following: Channel CapacityTheorem Given a source of M equally likely messages, with M1, which is generating information at a rate R. Given a channel with channel capacity C. Then, ifRCthere exists a coding technique such that the output of the source may be t

34、ransmitted over the channel with a probability of error in the received message which may be made arbitrarily small. The important feature of the theorem is that it indicates that for RC transmission may be accomplished without error in the presence of noise. This result is surprising. For in our co

35、nsideration of noise, say, gaussian noise, we have seen that the probability density of the noise extends to infinity. We should then imagine that there will be some times, however infrequent, when the noise must override the signal thereby resulting in errors. However, Shannons theorem says that th

36、is need not cause a message to be in error. Channel CapacityThere is a negative statement associated with Shannons theorem. It states the following: Theorem Given a source of M equally likely messages, with M1, which is generating information at a rate R; then if RC the probability the probability o

37、f error is close to unity for every possible set of M transmitter signals. This negative theorem states that if the information rate R exceeds a specified value C,the error probability will increase toward unity as M increases, and that also, generally, in this case where RC, increasing the complexi

38、ty of the coding results in an increase in the probability of error. . Capacity of a Gaussian Channel A theorem which is complementary to Shannons theorem and applies to a channel in which the noise is gaussian is known as the ShannonHartley theorem. Channel CapacityTheorem The channel capacity of a

39、 white, bandlimited gaussian channel is C=Blog2(1+S/N)bits/s(2.1)where B is the channel bandwidth, S is the signal power, and N is the total noise within the channel bandwidth, that is,N= B, with 1/2 the (two-ided) power spectral density. This theorem, although restricted to the gaussian channel, is

40、 of fundamental importance. First, we find that channels encountered in physical systems generally are, at least approximately, gaussian. Second, it turns out that the results obtained for a gaussian channel often provide a lower bound on the performance of asystem operating over a nongaussian chann

41、el. Thus, if a particular encoderdecoder is used with a gaussian channel and an error probability Pe results, then with a nongaussian channel another encoderdecoder can be designed so that the Pe will be smaller. We may note that channel capacity equations corresponding to Eq.(2.1) have been derived

42、 or a number of nongaussian channels. The derivation of Eq.(2.l) for the capacity of a gaussian channel is rather formidable and will not be undertaken. However, the result may be made to appear reasonable by the following considerations. Suppose that, for the purpose of transmission over the channe

43、l, the messages are represented by fixed voltage levels. Then, as the source generates one message after another in sequence, the transmitted signal s(t) takes on a waveform similar to that shown in Fig. 2.1. Channel Capacity. Please translate the following words and phrases into Chinese. 1. physica

44、l syste2. rise time 3. amount of information 4. in principle 5. gaussian channel 6. probability density 7. rootmeansquare 8. trade off 9. lower bound 1. equalizer 11. vice versa 12. upper limit Exercises物理系统，实际系统上升时间信息量理论上，原则上高斯信道概率密度均方根值, 均方根；均方根(的)交替换位，折衷选择下界, 下限均衡器反之亦然上限. Please translate the fol

45、lowing words and phrases into English.1. 通信理论2. 香农定理3. 信道带宽4. 信号波形5. 理想低通滤波器 6. 自相关函数7. 无噪声高斯信道 8. 通信信道9. 信息速率10. 信噪比Exercisescommunication theory(theory of communications)Shannons theoremchannel bandwidthsignal waveformideal lowpass filterautocorrelation functionnoiseless gaussian channelcommunicat

46、ion channelinformation rateSignal to noise ratio（SNR,S/N）Exercises11. 信道容量12. 双边功率谱密度13. 误码率14. 奈奎斯特采样速率15. 限带高斯信道16. 高斯白噪声channel capacityTwo sided power spectral densityerror probability (probability of error)Nyquist sampling rateband limited gaussian channelwhite Gaussian noiseExercises. Fill in

47、the blanks with the missing word(s). 1.There is a negative statement associated Shannons theorem.2. the purpose of transmission over the channel, the messages are represented by fixed voltage levels.3. Since the transmission of any of the M messages is equally likely,H=log2M,thus our channel is tran

48、sferring information a rate R=rH.4. For a fixed signal power and the presence of white gaussian noise the channel capacity approaches an upper limit with increasing bandwidth.5. It is great interest to recognize that the tradeoff between bandwidth and signal to noise ratio is not limited by a lower

49、limit bandwidth.withonatinofinExercises6. The signal is transmitted a channel which can be represented as a lowpass RC circuit with cutoff at 1 Hz.7. If there is no noise, then we are entirely free to make for the attenuation by the use of an amplifier and to correct the frequency distortion by the

50、use of an equalizer.8. That is, we need to estimate the interval T which should be assigned to each message to allow the transmitted levels to be recognized Individually the receiver, even though the bandwidth B of the channel is limited.9. Therefore, the 25 percent reduction bandwidth requires a 60

51、 percent increase signal power.inasinofoverExercises10. While we have used the term communication channel many occasions, it is well to emphasize at this point, that the term, which is Something an abstraction, is intended to encompass all the features and componentparts of the transmission system w

52、hich introduce noise or limit the bandwidth. 11. The probability of error is close unity for every possible set of M transmitter signals.12. It turns out the results obtained for a gaussian channel often provide a lower bound the performance of a system Operating a nongaussian hatintoinas

53、. Answer the following questions according to the text. 1.What is ShannonHartley theorem?2. Please describe Shannons theorem in your own words in English.ExercisesShannonHartley theorem:The channel capacity of a white,bandlimited gaussian channel is C=Blog2(1+S/N)bits/s,where B is the channel bandwi

54、dth,S is the signal power,and N is the total noise within thechannel bandwidth,that is,N=B,with /2 the (two sided) power spectral density.Given a source of M equally likely messages, with M1, which is generating information at a rate R. Given a channel with channel capacity C. Then, if RC,There exis

55、ts a coding technique such that the output of the source may be transmitted over the channel with a probability of error in the received message which may be made arbitrarily small.3. Try to describe Shannons theorem by a negative statement in English.4. Why is the ShannonHartley theorem important?E

56、xercisesThe ShannonHartley theorem, although restricted to the gaussian channel, is of fundamental importance. First, we find that channels encountered in physical systems generally are, at least approximately, gaussian. Second, it turns out that the results obtained for a gaussian channel often pro

57、vide a lower bound on the performance of a system operating over a nongaussian channel. Thus, if a particular encoderdecoder is used with a gaussian channel and an error probability Pe results, then with a nongaussian channel another encoder decoder can be designed so that the Pe will be smaller. Gi

58、ven a source of M equally likely messages, with M1, which is generating information at a rate R; then if RC, the probability of error is close to unity for every possible set of M transmitter signals.Exercises5. How can we trade off bandwidth for signaltonoise ratio according to the ShannonHartley p

59、rinciple?For example, if S/N=7 and B=4 kHz, we find C=12103bits/s. If the SNR is increased to S/N=15 and B decreased to 3 kHz, the channel capacity remains the same. With a 3 kHz bandwidth the noise power will be 3/4 as large as with 4 kHz. Thus the signal power will have to be increased by the fact

60、or B=3/415/7=1.6. Therefore, the 25 percent reduction in bandwidth requires a 60 percent increase in signal power.多媒体通信技术 孙学康New words and phrases1 analog(=analogue) n.模拟 2 quantization n.量化3 volt n.伏特4 discrete adj.离散的，不连续的 5 quantum n.量，量子,量子论 6 unipolar adj.单极的,单极性的7 polar adj.极性的,有两种相反性质的8 onoff