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信号与系统课程论文（报告、案例分析）

院系物理与电子工程学院

专业电子信息工程

班级 1211电工

学生姓名刘慧

学号 2012128040

任课教师罗倩倩

2014年 12 月 01 日

Liu Hui

Physics and Electronics Engineering College of Hubei University of

Arts and Science

1138804992@https://www.wendangku.net/doc/6f12003167.html,

Abstract：The characteristics of Butterworth filter is the pass band frequency response curves of the

maximally flat, no ups and downs, and in the resistance band is gradually decreased to zero. First order Butterworth filter attenuation rate of 6 dB per octave doubling every ten to 20 dB. The two order Butterworth filter attenuation rate of 12 dB per octave, and so on. The amplitude frequency monotone Butterworth filter down the diagonal, and whether the order number is unique, the amplitude frequency curves of the diagonal filter to keep the shape. But the higher the order of the filter, in the stop band

attenuation faster.

Key words:Butterworth passband frequency response sampling stopband

1 Requirements

using the impulse response method to design the Butterworth digital low pass filter, passband cutoff frequency 100HZ, the sampling frequency of 1000HZ, the maximum passband attenuation is 0.5HZ, minimum stopband attenuation i s 10HZ, the amplitude frequency and phase frequency, draw the corresponding curve. And the assumption of a signal x (T) =sin (2*pi*f1*t) +sin (2*pi*f2*t), wherein f1=50HZ, f2=200HZ. Use this signal to verify the correctness of filter design.

2 design principle

2.1 The basic concept of the digital filter

The so-called digital filter, refers to the input, output the digital signal, through numerical calculation processing relative proportion change of the input signal frequency components contained in, or filter in addition to certain frequency components of digital device or program, therefore, the concept of digital filter and analog filter is same, just form and realize the different filtering methods. Because of the digital filter to achieve filtering through numerical calculation, so the digital filter processing of high accuracy, stability, s mall volume and light weight, flexible, does not exist the problem of impedance matching, can special filtering function experiment simulation filter cannot achieve. If you want to deal with is the analog signal, through A\DC and D\AC conversion, matching in signal form, can also be filtered analog signal digital fi lter.

2.2 The working principle of the digital filter

Digital filter is a discrete time system, input x (n) is a time series, the output of Y (n) is a time series. Such as the system function of digital filter for H (Z), the pulse response of H (n), there is the following relationship in time domain;Y (n) =x (n)* H (n)

In the Z domain, the relationship between the input and output:Y (Z) =H (Z) *X (Z).In the formula, X (Z), Y (Z) x (n) respectively for the input and output y (n) Z transform.

Also in the frequency domain, the relationship between the input and output:Y (JW) =X (JW) *H (JW).In the formula, H (JW) for frequency response of digital filter, X (JW) and Y (JW) were x (n) and Y (n) spectrum. W is a digital angular frequency, unit rad. Usually the design of H (JW) in response to certain frequency value is 1, in response to certain frequency bands for 0.X (JW) and H (JW) of the product in the frequency response for 1 of those frequency value is X (JW), which can filter the unhindered by the amplitude of these bands, these bands for the pass band. X (JW) and H (JW) product response to those of 0 frequency value regardless of the X in the frequency band (JW) size is zero, which is not in the amplitude in these bands through the filter, the band called the stopband.

A suitable digital filter system function H (Z) may according to need to input x (n) frequency characteristic, the Y processed signal digital filter after the (n) retention signal x (n) useful frequency component in the removal of unwanted frequency components.

2.3 Butterworth filter design principle

2.3.1 the basic properties

Butterworth filter with the Butterworth function to approximate the system function filter. Butterworth filter is a filter according to the amplitude frequency characteristics has the most flat characteristics defined in the pass band..

The following summarizes the main characteristics of Butterworth filter

A .on all N,.()

1a j H 20=Ω=Ω B. on all N,()

707.0a j 2c =ΩΩH =Ω ()dB 3a lg 20j H c

=Ω=ΩΩ C .

()Ωj H a 2is monotone decreasing function. D. ()Ωj H a 2

with the increase of order N and more close to the ideal lowpass filter. As shown in Figure 2, we can see that the amplitude frequency characteristic of filter with order N filter increase and become better and better in the cut-off frequency Ωa function at C value is always 1/2, pass band more band area is close to 1; within the stopband more rapidly approaching zero.

Figure 2 Butterworth low pass filter amplitude frequency characteristics of the square

2.3.2 the system function

The system function design for Ha Butterworth (s), then:

2.3.3 the design process

Butterworth low pass type relation index filtering technology

Ap>-20log|Ha (J) |,

Ωa < ΩaP As<-20log|Ha (J) |, Ωa > Ωas Of which: ΩP

passband

boundary frequency, Ωa s stopband edge frequency. The type 1.4.1 can be:

After simplification finishing available:

For the smallest integer N type as the order of the filter. Then N into available:

The look-up table to obtain normalized transfer function H (s), make s/ Ωa C instead of normalized prototype filter system function s, to obtain the actual filter transfer function.

2.4 he impulse response method

The so-called impulse response method is the digital filter impulse response sequence H (n) in response to the HA is equal to the analog filter (T) value of the sample, i.e.

H (n) =ha (T) |t=nT=ha (nT)

In the formula, T is the sampling period.

Therefore, digital filter system function H (Z) can be calculated by the formula

H (z) =Z[h (n)]=Z[ha (nT)]

Z[-] said the content of transform transform [-], please refer to the contents of the digital signal processing of the corresponding materials.

If you have already acquired the meet the transfer function of the Ha analog filter performance index (s), the H digital filter transfer function for the corresponding (z) method is the:

(1), for analog filter unit impulse response ha (t).

In the formula, L[Ha (s)] Ha (s) expressed the Laplace. inversion. Laplace transform, please refer to the contents of the integral transform or signal processing teaching of higher mathematics.

(2), for analog filter unit impulse response ha (T) sampling values, namely digital filter impulse response sequence H (n).

(3), rushed to the digital filter (n) response of the Z transform, transfer function H (Z).

By the above method to infer more directly by analog filter system function Ha (s) to calculate the digital filter system function H (z) steps:

(1) the use of the partial fraction expansion of the transfer function of the H analog filter (z) is expanded into

Ha (s) = Rk\ (S-Pk)

In MA TLAB this step can be implemented by residue function

If you call the residue function is of the form [b (R, a]=residue, P, K) form.

If [R, P, K]=residue (a, b) is the reverse process of the above call form.

(2) the Pk transform for the digital simulation of pole pole e^pkT to obtain the transfer function of the digital system

H (z) = Rk\ (1-e^pkT*z* (-1))

Type T is the sampling interval.

(3) the type conversion to transfer function form, can use [R, P, K]=residue (B, a).

For the above steps, has provided the impulse response function method to design digital filter, call format

[bz, az]=impinvar (B, a[, Fs], Fp)

In the formula, B, a analog filter the numerator and denominator polynomial coefficient vector; Fs is the sampling frequency (the filter data), unit Hz, the default for 1Hz, pre distortion frequency (prewarped frequency), is a "match" in frequency, the frequency, frequency response and the change before and after the simulation of frequency in the the variable can be matched precisely. Do not consider the general design. BZ, AZ respectively for the digital filter the numerator and denominator polynomial coefficient vector.

2.5 the MATLAB function that number.

(1) [N, wc]=buttord (WP, WS, RP, As, 's')

The format used in the order of N and 3dB to calculate Butterworth analog filter cutoff frequency wc. Wp, WS and WC is the actual simulation of the angular frequency (rad\s). Rp and As for the maximum passband attenuation and minimum attenuation.

(2) [Z, P, k]=buttap (N)

The format used in the calculation of N order Butterworth normalized analog low pass prototype filter system function zeros and poles and the gain factor returns the length of the N column vectors Z and P, were given N a zero and pole position, said K filter gain.

(3) Y=filter (B, a, x)

Type B said in the coefficient matrix of the system transfer function of the numerator polynomial coefficient matrix; a represents the denominator polynomial of the system transfer function; X represents the input sequence; filter represents the output sequence. A direct form of IIR functions.

(4) [b, a]=butter (N,Ωc, 'ftype')

The coefficient vector calculation of N order Butterworth digital filter system function the numerator and denominator polynomials B, a.

Note: the order number and the call to 3dB parameters N and WC are respectively the Butterworth digital filter cutoff frequency normalized value is generally called buttord format (1) calculation of N and wc. Coefficient b, a is in accordance with the Z-1 power arrangement.

(5) [B, A]=butter (N, Ωc 'ftype', 's')

Calculation of molecular, Butterworth analog filter system function of the denominator polynomial coefficient vector.

Description: C respectively as the Butterworth simulation filter call parameters N and Ωorder and 3dB cutoff frequency (the actual angular frequency), call the buttord (2) N and Ωc format calculation. Coefficients B, A are arranged according to descending s.

Tfype is a type of filter:

Ftype=high, high pass;Ωc only 1 values.

Ftype=stop, band stop; Ωc=[Cl, Omega cu], respectively, band stop filter passband 3dB cutoff frequency and the upper cutoff frequency.

Ftype by default: if Ωc only 1 values, the default is low pass; if Ωc2 values, the default is bandpass; the pass band frequency interval Ωc1< Ωa < Ωcu.

(6) [H, w]=freqz (B, a, N)

The coefficient vector B and a respectively for the discrete system system function the numerator and denominator polynomial, back H consists of discrete frequency response in the range of 0 ~ PI N frequency points values (where N is a positive integer), the w contains a frequency range of N points. Call the default N, 512 of its value. Can call freqz () calculation of frequency response function of the system, and then use the ABS () and angle () function and plot () function, draw out the frequency response curve of system.

(7) the lp2lp function [bt, at]=lp2lp (B, a, W0)

The function used to achieve the frequency transform by the low pass analog low-pass filter prototype filter, can be used to transfer function and the state space conversion, but no matter what kind of form, the input must be the analog filter prototype.

(8) [bz, az]=impinvar (B, a, FS)

With [b, the a] simulation of the filter transfer function model is converted into the sampling frequency

3 design ideas

Set signal

↓Analog low-pass filter prototype→frequency conversion→ analog discrete→IIR digital filter→the output signal

4 the design content

4.1MATLAB program design

Wp=2*pi*100; Ws=2*pi*150; % filter cutoff frequency

Rp=0.5; Rs=10; % maximum passband attenuation and the minimum stopband attenuation

Fs=1000 % of the sampling frequency;

Nn=128; % frequency points used by calling freqz

[N, Wc]=buttord (Wp, Ws, Rp, Rs,'s'); % minimum order analog filter number

[z, P, k]=buttap (N); % design analog lowpass Butterworth filter

[Bap, Aap]=zp2tf (Z, P, K); % converts the zero pole gain form as the form of transfer function [b, a]=lp2lp (Bap, Aap, Wc) % for frequency conversion

[bz, az]=impinvar (B, a, Fs); % by using the impulse response method to obtain the transfer function of the digital filter

Figure (1)

[H, W]=freqz (BZ, AZ, Nn, Fs); % amplitude characteristic drawing of digital filter and the phase frequency characteristic

Subplot (2,1,1)

Plot (W, 20*log10 (ABS (H)));

Xlabel ('frequency');

Ylabel ('range');

Grid on;

Subplot (2,1,2);

Plot (W, 180\pi*unwrap (angle (H)));

Xlabel ('frequency');

Ylabel ('range');

Grid on;

Figure (2)

F1=50; f2=200; % of the input signal frequency

N=100; % data length

Dt=1\Fs; n=0:N-1; t=n*dt; % sampling interval and time series

X=sin (2*pi*f1*t) +sin (2*pi*f2*t) % filter input signal

Subplot (2,1,1); % to draw the input signal

Plot (T, X);

Title ('input signals'); % on the input signal filtering using filter function y1=filter (BZ, AZ, X); Subplot (2,1,2); % plotted output waveform

Xlabel ('time')

Title ('output signal');

4.2 Experiment results and analysis

The two picture as obtained from the experiment shown in the first picture, less than 100 attenuation is less than 3Hz, and in the greater than 120Hz attenuation greater than 15dB, meet the design index filter. By the second pictures to see signal on 50Hz and 200Hz frequency components of the filter, filter the 200dB signal, achieve the effect of filtering.

5 The experience of experiment

Program the simulation process, I found the function and based on the low-pass filter to the design I. According to the design of the filter of the WP, WS, Rp, Rs four parameters to determine the frequency of the input signal in order to achieve the purpose of filtering. I also meet a lot of problems in the course of the experiment, but through the search data have been resolved. Through the curriculum design of learning, we have the simulation and design of MA TLAB, enhance mutual understanding and technical indexes of the low pass filter design principle of setting. The curriculum design not only let me on the digital signal processing theory of knowledge of the discipline to deepen understanding, but also let me use for many of the functions in the MA TLAB is more flexible, but also enhances the ability to solve the problem .

6 Ref.

[1] digital signal processing "(Third Edition) Gao Xiquan Ding Meiyu, Xi'an Electronic and Science University press

[2] "MA TLAB toolbox application" Su Jinming Zhang Lianhua Paul Liu, publishing house of electronics industry

[3] "digital signal processing MA TLAB implementation" edited by Wan Y ongji Science Press

科技英语论文

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科技英语论文实用写作学习心得 (5000字)

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科技论文写作英语写作

Research Reports for Business and Technical Writing Wayne Losano A surprising amount of one's time as a student and professional is spent reporting the results of one's research projects for presentation to teachers, managers, and clients. Indeed, without basic research skills and the ability to present research results clearly and completely, an individual will encounter many obstacles in school and on the job. The need for some research-writing ability is felt nearly equally by college students in all fields, engineering and science as well as business and the humanities. Graduate study often makes great demands on the student's research-writing skills, and most professions continue the demand; education, advertising and marketing, economics and accounting, science and engineering, psychology, anthropology, the arts, and agriculture may all require regular reporting of research data. ELEMENTS OF THE RESEARCH PAPER The standard research report, regardless of the field or the intended reader, contains four major sections. These sections may be broken down into a variety of subsections, and they may be arranged in a

【免费下载】中英文科技论文写作教程

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ON-LINE DIAGNOSIS OF MARINE DIESEL CRANKSHAFT CRACK BASED ON MAGNETIC MEMORY* LI HAN-LIN, LIN JIN-BIAO, CAI ZHEN-XIONG, LU YONG (Marine Engineering Institute, Jimei University, Xiamen, Fujian 361021) Abstract: This paper summarized recent diagnosis methods of marine diesel crankshaft crack and introduced the fundamental principle, development and application of metal magnetic memory testing (MMMT) diagnosis technology. Compared with other methods, a scheme developed from MMMT combined with torsional signal to make on-line diagnosis of crankshaft crack was proposed, and the on-line diagnosis experimental platform of diesel was designed. Finally, comments were also made on the on-line MMMT method. Keywords: marine diesel; crankshaft; crack; metal magnetic memory 1Introduction Most of the crankshaft cracks on ocean marine diesel are deeply latent and difficult to detect artificially. In general, while the crack develops to a certain extent it will rupture and cause destructive breakage1. If inchoate stress concentration and tiny crack of crankshaft are detected on-line by Non-Destructive Testing (NDT) methods, the diesel can be stopped before the full development of the crack and thus rupture can be avoided. A new NDT method, MMMT developed rapidly recent years with advantages in such areas as cheap and simple sensors, measuring without impacting diesel operation and long-term on-line detection. Therefore, there will be a great foreground to use MMMT in crankshaft crack detection. 2Dynamic Diagnosis of Crankshaft Crack 2.1 Static Diagnosis of Crankshaft Crack Crankshaft crack is one of the fatal faults in diesels. There are some static NDT methods to diagnose crankshaft crack2such as Ultrasonic Testing, Radiographic Testing, Magnetic Particle Testing, Penetrate Testing, Eddy Current Testing, Optical Holography,and Microwave Testing. These methods have taken an important part in crankshaft quality control and accident prevention. However, on the other hand there are several disadvantages of these methods. Firstly, all of them must find cracks already formed and can not detect unexpected ones. Secondly, they are unable to make on-line detection and fault diagnosis. Thirdly, most of them need surface pretreatment of the facilities before inspection. Finally, the accuracy of detection is affected by crankshaft configuration and personal skill. 2.2 Dynamic Diagnosis of Crankshaft Crack At present there are some methods to diagnose shaft cracks on-line: rotor engine vibration displacement method, train wheel shaft temperature testing, acoustic emission and tortional vibration signal testing. However, vibration displacement method is unfit for diesel crankshaft crack diagnosis due to the strong vibration from reciprocating movement which makes it difficult to survey displacement and acceleration. Although there is local high temperature on the cracks, it is hard to inspect the change of the crankshaft temperature due to the high temperature of the lube oil in the diesels. Acoustic emission method is still in developing as great noise from diesel operation makes it difficult to measure high frequency acoustic wave emitted by crack. Therefore at present it is feasible to diagnose crankshaft crack on-line by using torsional vibration signal. * This research is supported by Nature Science Funding Project of Fujian Province A0410022.

英语科技论文

英语科技论文 China's energy security problems and response measures Wufei Qin (Guangxi University Materials Science and Engineering) Nanning,Guangxi 530004 Abstract: With economic development and industrialization, accelerated urbanization, China's growing demand for energy, but many are non-renewable energy, we also face the serious problem of energy shortage. In this paper, in several aspects of energy security, China is faced with major issues and solve the energy crisis caused by a variety of measures. Key words: Energy Energy crisis Energy Technology In the 21st century, China's national economy maintained strong momentum of rapid development.People's living standards are improving. And the demand for energy is increasing, Our contry’s oil production of about 165 million tons, 1.6 billion tons of coal production, but still can not meet the national economy the needs of rapid development, China has become a net oil importing countries, imports of 9000-10000 tons of oil annually. The world also face the grim situation of energy https://www.wendangku.net/doc/6f12003167.html,cking of energy may cause serious consequences, we must have a clear head, a sense of crisis and urgency. 1 The problems of energy security of our country

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Research on Trigonometric Leveling Freedu School of Geodesy and Geomatics, Wuhan University,Wuhan430079,China E-mail:1111111111@https://www.wendangku.net/doc/6f12003167.html, Abstract —As the total station trigonometric leveling can survey without the restrictions oftopography. So, we can use it to survey the third &fourth order level survey in some special areas.In this article, we propose a new total station measuring method from combining the defect of traditional measurementmethods. The advantages of this method is that it can improve the precision without measuring height of device and prism, and it canreplace the third and fourth level of measurement under certain conditions. This method can greatly improve efficiency and shortenthe project duration in the construction survey ． Keywords- trigonometric leveling ；total station ；error analysis I. I NTRODUCTION Engineering construction often relates to height measurement. Thetraditional measurement methods are leveling surveying andtrigonometry trigonometric leveling. Although the two methods have their own characteristics, but there are shortcomings.With the widespread use of the Total Station and using the track rod with the total station method to measure the elevation of the increasingly popular, traditional trigonometric leveling method has shown its limitations.After a long journey, a new trigonometric leveling method has been summed up.This approach combines the advantages of two traditional approaches to further improve the accuracy of the trigonometric leveling and tosurvey faster. This article systematically expounds the principle of traditional trigonometric leveling methods and the new methods, compares their advantages and disadvantages, and analyses the main errors and measurement accuracy in the process of trigonometric leveling. II. P RINCIPLE OF T RADITIONAL T RIGONOMETRIC L EVELING AND THE N EW M ETHOD The basic formula of the traditional trigonometric leveling: tan B A H H D i t α=++- (1) where A H is the elevation of a known point, B H is the elevation of the unknown point, D is the horizontal distance between the two points, αis the vertical angle when observe from point A to point B,i is instrument height, t is the height of the prism. For traditional methods, total station must be set up in the known elevation point. At the same time, you must measure out the height ofboth the instrument and the prism if you want to measure the elevation of the unknown points. If we can measure the elevation of the measured point while set point of total station arbitrarily like leveling surveying, instead of set it on a known elevation point, and do not measure out instrument and prism,speed of measurement will be faster. As shown in the figure 1, assuming that the elevation of the point A is known, the elevation of the point B is unknown, here we measurethe elevation of other points by total station. Figure 1. Diagram for trigonometric leveling Firstly, seen by trigonometric leveling principle: (tan )B A H H D i t α=-+- (2) where i, t is unknown, but one thing is sure that once the instrument set, value of i will remain unchanged.At the same time choose tracking lever as a reflecting prism, assume that the value of t is also fixed. Seen from formula (2), tan B A H i t H D W α+-=-= (3) By formula (3),the value of W will remain unchanged in any station. And while both A H and tan D αare known, it is possible to calculate the value of W . Operation of this new method is as follows: Shown in Figure 2, elevation of point A is known, elevation of point B is unknown, and the instrument is set up at point C between A and B. The instruments sight point A to get the reading 1V . That 1V =1D 1tan α, and calculate the value of W, W = A H +1D 1tan α. At this time related constants such as elevation of station, instrument height and prism height can beof any value, not necessary to set before measuring. And then set elevation of point Cto W , set the instrument height and prism height to 0. Then elevation of point C is known. Finally sight the target point B and measured its elevation, that is 22tan B H W D α=+ (4) Therefore, using the new method, elevation of point B is 1122tan tan B A H H D D αα=-+ (5)

英语科技论文写作

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写好英语科技论文的诀窍(周耀旗)

写好英语科技论文的诀窍：主动迎合读者期望，预先回答专家可能质疑周耀旗印地安那大学信息学院印地安那大学医学院计算生物学和生物信息中心以此文献给母校中国科技大学五十周年校庆前言我的第一篇英语科技论文写作是把在科大的学士毕业论文翻译成英文。当我一九九零年从纽约州立大学博士毕业时，发表了20多篇英语论文。但是，我对怎样写高质量科技论文的理解仍旧处于初级阶段，仅知道尽量减少语法错误。之所以如此，是因为大多数时间我都欣然接受我的博士指导老师Dr. George Stell和Dr. Harold Friedman的修改，而不知道为什么要那样改，也没有主动去问。这种情况一直持续到我去北卡州立大学做博士后。我的博士后指导老师Dr. Carol Hall建议我到邻近的杜克大学去参加一个为期两天的写作短训班。这堂由Gopen教授主办的短训班真使我茅塞顿开。第一次，我知道了读者在阅读中有他们的期望，要想写好科技论文，最有效的方法是要迎合他们的期望。这堂写作课帮我成功地完成了我的第一个博士后基金申请，有机会进入哈佛大学Dr. Martin Karplus组。在哈佛大学的五年期间，在Karplus教授的指导下，我认识到一篇好的论文需要从深度广度进行里里外外自我审查。目前，我自己当了教授，有了自己的科研组，也常常审稿。我觉得有必要让我的博士生和博士后学好写作。我不认为我自己是写作专家。我的论文也常常因为这样或那样的原因被退稿。但是我认为和大家共享我对写作的理解和我写作的经验教训，也许大家会少走一些我走过的弯路。由于多年未用中文写作，请大家多多指正。来信请寄：yqzhou@https://www.wendangku.net/doc/6f12003167.html,。欢迎访问我的网站：https://www.wendangku.net/doc/6f12003167.html,。导言通常来讲，研究生和博士后从他的导师那儿得到研究方向。经过多次反复试验，得到一些好的结果。接下来他们需要对得到的数据进行总结和分析，写成论文。一篇精写的论文更容易被高档杂志接受。而写得不好的论文很可能被退稿。论文的数量和质量是学生和导师事业发展的敲门砖。不成文，便成仁，是学术生涯的写照。很多学生以为当结果到手的时候研究就结束了。他们写的草稿，常常把原始数据放在一起，没有对方法和数据进行详细分析，没有对当今论文的评述。事实上，写作是研究不可分割的一部分。此刻是弄懂方法的成功与失败，寻找结果的解释及其隐含的意义，以及与其他相关研究进行比较的时候。我们为什么需要在写作上如此认真努力？原因很简单。一个研究结果只有在被别人使用时才有意义。而想被别人使用，文章必须能引起其他科学家的兴趣，而且得保证其他人能看懂并可以重复和再现你的结果。只有可以被理解的研究才会被重复，也只有可以被再现的工作才能导致别人的引用和跟踪。而你的论文被引用的数量常常用来衡量研究的影响力。从某种角度看，写作就象是把你的工作成果推销给其他的科学家。为了更好的推销，科学论文必须满足它独特的顾客：由聪明能干的科学家组成的尖端读者。它必须能先说服（通常也是竞争对手的）同行们，因为他们的评审是文章在发表前的第一道关口。同时，它也必须满足一般读者的要求。为了达到这个目标，我们首先要理解他们需要什么？读者需要什么你的文章的潜在读者可能有刚进入这领域的新手，大学生和研究生，也有专家（潜在审稿人)，他们对你的领