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- An estimator is a random variable. 估計量是一個(gè)隨機變量。
- W is a zero mean white noise source. W是一個(gè)零均值的白噪聲源。
- The expected value of a random variable. 期望值隨意可。
- The discrete random numbers is generated from a continuous pseudo random variable scaled by rng, mean shifted by vsh and dicretized by step size drv. 離散隨機數值取自一連續隨機變數乘以縮放比、并以等階梯大小離散化及平均值位移而得。
- This paper presents a reliability design method for fatigue strength of steam turbine parts subjected to alternating and mean stess with random variable stress ratio. 本文介紹了應力幅和平均應力之比為隨機變量時(shí)汽輪機零件疲勞強度的可靠性設計方法。
- Do The Function of A Continuous Type of Random Variable Also Belong To One? 連續型隨機變量的函數還是連續型隨機變量嗎?
- The key is the notion of a discrete quantization of a random variable X. 其中的關(guān)鍵是對一個(gè)隨機變量X進(jìn)行的離散量化的概念。
- In this study, those remaining effects are treated asstochastic noise and are assumed white Caussian distributed with zero mean. 在這項研究中,那些未被考慮的各影響因素被作為隨時(shí)噪聲加以處理,并假設其具有零均值白高斯分布。
- Kurtosis is a classical measure of non-Gaussianity of random variable. 峭度是隨機變量非高斯性的一個(gè)經(jīng)典度量。
- In this example for that X is a zero mean uniform R.V, Y is a zero mean uniform R.V, U is the difference of R.V.X, Y, and V is the product of R.V. 本文以甲變數為均勻隨機變數，乙變數為均勻隨機變數，丙變數為甲乙隨機變數之差，及丁變數為甲乙隨機變數之積的情況下，圖示驗證二維隨機變數聯(lián)合機率之特性。
- The mean of a random variable. 隨意可變量
- In this example for that X is the product of zero mean uniform R.V.Urn0, Y is a zero mean uniform R.V, U is the cosine of product of R.V.X, Y, and V is the difference of R.V. 本文以甲變數為均勻隨機變數之積，乙變數為均勻隨機變數，丙變數為甲乙隨機變數積之馀弦，及丁變數為甲乙隨機變數之的差情況下，圖示驗證二維隨機變數聯(lián)合機率之特性。
- In this example for that X is a zero mean uniform R.V, Y is the product of zero mean uniform R.V.Urn0, U is the sum of R.V.X, Y, and V is the cosine of product of R.V. 本文以甲變數為均勻隨機變數，乙變數為均勻隨機變數之積，丙變數為甲乙隨機變數之和，及丁變數為甲乙隨機變數積之馀弦的情況下，圖示驗證二維隨機變數聯(lián)合機率之特性。
- A random variable with a numerical value that is defined on a given sample space. 隨機變量在給定的樣本空間內定義的，具有一個(gè)數值的隨機變量
- In this example for that X is the sum of zero mean uniform R.V.Urn0, Y is the cosine of zero mean uniform R.V.Urn0, U is the product of R.V.X, Y, and V is the sum of R.V. 本文以甲變數為均勻隨機變數之和，乙變數為均勻隨機變數之馀弦，丙變數為甲乙隨機變數之積，及丁變數為甲乙隨機變數之和的情況下，圖示驗證二維隨機變數聯(lián)合機率之特性。
- In this example for that X is a zero mean normal R.V, Y is the product of zero mean uniform R.V.Urn0, U is the even exponential of sum of R.V.X, Y, and V is the product of R.V. 本文以甲變數為均勻隨機變數，乙變數為均勻隨機變數之積，丙變數為甲乙隨機變數和之偶指數函數，及丁變數為甲乙隨機變數之積的情況下，圖示驗證二維隨機變數聯(lián)合機率之特性。
- Property of symmetric random variable is discussed by introducing the concept of almost supremum and infimum. 討論了具有倒對稱(chēng)隨機變量的若干性質(zhì).
- In this example for that X is the sum of zero mean uniform R.V.Urn0, Y is a zero mean uniform R.V, U is the product of R.V.X, Y, and V is the difference of R.V. 本文以甲變數為均勻隨機變數之和，乙變數為均勻隨機變數，丙變數為甲乙隨機變數之積，及丁變數為甲乙隨機變數之的差情況下，圖示驗證二維隨機變數聯(lián)合機率之特性。
- Cumulate probability distribution of trials of random variable of bathtub (or M) distribution. 隨機變數多次試驗結果之累積機率為兩極化分布。
- In this example for that X is a zero mean normal R.V, Y is the cosine of zero mean uniform R.V.Urn0, U is the even exponential of sum of R.V.X, Y, and V is the difference of R.V. 本文以甲變數為均勻隨機變數，乙變數為均勻隨機變數之馀弦，丙變數為甲乙隨機變數和之偶指數函數，及丁變數為甲乙隨機變數之的差情況下，圖示驗證二維隨機變數聯(lián)合機率之特性。
