翻译-中翻英

翻译-中翻英

1st, only gives the function value the signal in certain not continual instants, becomes the discrete time signal. It may come from the simulated signal sampling, or is the time and the scope not continual discrete signal. When discrete signal analysis and processing, usually presses certain priority order to arrange in the time not a continual number of classes set, calls it the sequence. 2, two different sequences may correspond the same Z transformation, but the convergence domain is not same, therefore, to cause the sequence and the Z transformation is 11 correspondences, while gives the sequence Z transformation, must assign its convergence domain. 3, the random signal cannot use the precise mathematics relationship description the signal, but its change obedience statistics rule, may use the probability statistical property to describe. Each vice minister who does according to the time course the time observation record is called the sample function immediately to the signal. 4, random signal's time domain and the frequency range characteristic may use the statistical method to conduct the research, its peak-to-peak value characteristic uses the signal the average value, the mean square value and the probability density function expression. The signal time domain characteristic may also use the autocorrelation function to describe, the frequency range characteristic may use the power spectral density function to describe

1, The signal only in certain discrete functions are given the instantaneous value and become discrete-time signal. It can come from a sample of the analog signal, or the rate of time and not in a row of discrete signals. In the discrete signals analysis and processing , Usually by a certain order in time in a row is not a group of several collections, called the series.
2, two different sequences can be the same as the corresponding Z transform, and the convergence of different domains, in order to make the series and Z-one mapping is a transformation in the transformation of the Z series is given at the same time, we must specify the convergence domain.
3, random signal is not precise mathematical description of the relationship between the type of signal, but it's subject to change in the law of statistics, probability and statistics can be used to describe characteristics. Immediately to the signal time course of doing all the long record of the observation function as the sample.
4, random signals in the time domain and frequency domain characteristics can be used statistical methods to study, the amplitude of the signal characteristics of the mean, mean square value and probability density function. The time-domain signal characteristics can also be used to describe auto-correlation function, the frequency characteristics can be used to describe the power spectral density function.

1, a signal being put up the function value only in some discontinuous microtime , becomes straggling time signal. It can come from the analog signal sampling , be time and without exception discontinuous extent scattering signal or. During the period of scattering signal analysis and treatment , generally with arranging aggregation mounting discontinuous group of number in time according to certain precedence , being called progression. Different 2, two arrays can be corresponding identical Z varies, but the convergence region is not same as, therefore, for making the array and Z vary is one to one correspondence, must assign the person to restrain self's a region while giving array Z out alternation. The random signal can use the signal that accurate mathematics relational expression describes 3, its alteration obedience counts but a law , can use probability statistics to describe that coming characteristic property. The signal is called the sample book function face to face immediately according to precis writer made by time course. Random signal time domain and frequency region characteristic property can use statistical method to be in progress studying 4, whose amplitude characteristic property uses the signal mean value , mean square value and probability density function indicate that. Signal time domain characteristic property also can use self relevance function to describe that , frequency region characteristic property can use power spectrum density function to describe that.

又一个电子信息的孩子。。
一句句翻译太麻烦了 给你key word吧，其他组织一下就好了
离散时间 discrete time
模拟信号 analog signal
抽样 sampling
幅度 magnitude
Z变换 z transform
收敛域 the region of convergence
随即信号 ramdon signal
时域 time domain
频域 frequency domain
功率谱 power spectrum

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