Search results for "Variance" - Rhea

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• Test
  ...hen the variances of two categories differ. In previous examples where the variance for both categories are the same, the Chernoff bound was close to the Bhatt
  17 KB (2,590 words) - 10:45, 22 January 2015
• Probability Formulas
  ...oz-background-inline-policy: -moz-initial;" colspan="2" | Expectation and Variance of Random Variables
  3 KB (491 words) - 12:54, 3 March 2015
• Bayes Rate Fallacy: Bayes Rules under Severe Class Imbalance
  ...o-able, since the abnomal sample is made far apart enough (compared to the variance of class1), but in the second example, it's just not possible to ditinguish
  5 KB (694 words) - 12:41, 2 February 2012
• Lecture11ECE662S10
  ...nown. Finally, we looked at the slight "bias" problem when calculating the variance.
  833 B (115 words) - 09:15, 11 May 2010
• Noteslecture11ECE662S10
  '''Example 2: 1D Gaussian with unknown mean and variance''' ...t{\Sigma}</math> over all data sets of size <math>N</math> is not the true variance <math>\Sigma</math>.
  7 KB (1,179 words) - 09:17, 11 May 2010
• Snikitha ListECE302
  <br/><br/>5. Expected value (used in ECE 438), variance (used in ECE 438) <br/><br/>6. Conditional/total pdf, pmf, expectation, variance
  2 KB (231 words) - 07:20, 4 May 2010
• Noteslecture8ECE662S10
  ...distributed variables (i.i.d) with finite mean <math>\mu</math> and finite variance <math>\sigma^2>0</math>.Then as n increases the distribution of <math>\Sigm Xi has mean <math>\mu_i</math> and finite variance <math>\sigma^2 > 0</math> ,i=1,2,...,n
  5 KB (806 words) - 09:08, 11 May 2010
• Decision Theory Glossary ECE662Spring2008
  ...y Fisher's criterion, which applies exactly to Gaussian classes with equal variance and approximately to other models. Variants like Flexible discriminant anal ...zes the distance between the means of the two classes while minimizing the variance within each class. See Lecture 10 for detailed explanation.
  31 KB (4,787 words) - 18:21, 22 October 2010
• ECE PhD QE CNSIP 2001 Problem1.3
  ...nt, but that each have identical mean <math class="inline">\mu</math> and variance <math class="inline">\sigma^{2}</math> . Let <math class="inline">\mathbf{Y
  5 KB (928 words) - 17:46, 13 March 2015
• ECE600 Example Two jointly distributed random variables
  and <math>\mathbf{Y}</math> is a Gaussian random variable with mean 0 and variance 1. Let <math>\mathbf{U}</math> and <math>\mathbf{V}</math> be two new rando
  7 KB (1,103 words) - 05:27, 15 November 2010
• ECE600 Note Chebyshev inequality
  ...ath>\mathbf{X}</math> be a random variable with mean <math>\mu</math> and variance <math>\sigma^{2}</math>. Then <math>\forall\epsilon>0</math>
  3 KB (437 words) - 11:26, 16 November 2010
• ECE600 Example Addition of two independent Gaussian random variables
  What kind of pdf is the pdf you determined in part (b)? What is the mean and variance of a random variable with this pdf? ...}}^{2}}{\sigma_{\mathbf{X}}^{2}+\sigma_{\mathbf{N}}^{2}}\cdot y</math> and variance <math>\frac{\sigma_{\mathbf{X}}^{2}\sigma_{\mathbf{N}}^{2}}{\sigma_{\mathbf
  6 KB (939 words) - 04:20, 15 November 2010
• ECE 600 Prerequisites Discrete Random Variables
  ='''1.4.4 Poisson distribution when mean and variance are <math class="inline">\lambda</math>'''=
  5 KB (921 words) - 11:25, 30 November 2010
• ECE 600 Prerequisites Some Measures of Random Variables
  1.8.2 Variance
  2 KB (305 words) - 11:15, 17 November 2010
• ECE 600 Chebyshev Inequality
  ...math> be a random variable with mean <math class="inline">\mu</math> and variance <math class="inline">\sigma^{2}</math> . Then <math class="inline">\forall\
  3 KB (435 words) - 11:38, 30 November 2010
• ECE 600 Weak law of large numbers
  ...d.</math> random variables with mean <math class="inline">\mu</math> and variance <math class="inline">\sigma^{2}</math> . Define <math class="inline">\mathb You can show this is true as long as the mean exists. The variance need not exist. Proof for this is harder and not responsible for this.
  2 KB (303 words) - 11:39, 30 November 2010
• ECE 600 Strong law of large numbers (Borel)
  ...istributed random variables with mean <math class="inline">\mu</math> and variance <math class="inline">\sigma^{2}</math> , and <math class="inline">Cov\left(
  795 B (126 words) - 11:41, 30 November 2010
• ECE 600 Central Limit Theorem
  ...''d''.</span> random vectors with mean <span class="texhtml">μ</span> and variance <span class="texhtml">σ²</span> , such that <span class="texhtm ...le <math class="inline">\mathbf{Z}</math> that is Gaussian with mean 0 and variance 1 .
  4 KB (657 words) - 11:42, 30 November 2010
• ECE 600 General Concepts of Stochastic Processes Systems with Stochastic Inputs
  ...{A}</math> has a mean <math class="inline">\mu_{\mathbf{A}}</math> and a variance <math class="inline">\sigma_{\mathbf{A}}^{2}</math> . Is <math class="inlin
  11 KB (1,964 words) - 11:52, 30 November 2010
• ECE 600 Homework
  ...h class="inline">\mathbf{X}_{k}</math> are independent with zero mean and variance <math class="inline">\sigma_{k}^{2}</math> , then the sum exists in the MS
  5 KB (859 words) - 11:55, 30 November 2010
• ECE 600 Finals MRB 1994 Final
  ...<math class="inline">\mathbf{X}</math> be a random variable with mean 2 , variance 8 , and moment generating function <math class="inline">\phi_{\mathbf{X}}\l (b) Find the variance of <math class="inline">\mathbf{X}\left(t\right)</math> .
  22 KB (3,780 words) - 07:18, 1 December 2010
• ECE 600 Finals MRB 2004 Final
  (c) Find the variance of <math class="inline">\mathbf{M}</math> .
  12 KB (2,205 words) - 07:20, 1 December 2010
• ECE600 QE 2001 January
  Find the mean and variance of the output.
  6 KB (1,093 words) - 08:23, 27 June 2012
• ECE600 QE 2001 August
  ...nt, but that each have identical mean <math class="inline">\mu</math> and variance <math class="inline">\sigma^{2}</math> . Let <math class="inline">\mathbf{Y Find the mean and variance of <math class="inline">\mathbf{X}\left(t\right)</math> .
  10 KB (1,827 words) - 08:33, 27 June 2012
• ECE600 QE 2002 August
  ...thbf{X}</math> has mean <math class="inline">\mu_{\mathbf{X}}</math> and variance <math class="inline">\sigma_{\mathbf{X}}^{2}</math> . The correlation coeff ...mean <math class="inline">a\mu_{\mathbf{X}}+b\mu_{\mathbf{Y}}</math> and variance <math class="inline">a^{2}\sigma_{\mathbf{X}}^{2}+2rab\sigma_{\mathbf{X}}\s
  10 KB (1,652 words) - 08:32, 27 June 2012
• ECE600 QE 2003 January
  ...bf{M}=\frac{\mathbf{X}+\mathbf{Y}}{2}</math> is independent of the sample variance <math class="inline">\mathbf{V}=\left(\mathbf{X}-\mathbf{M}\right)^{2}+\lef If <math class="inline">\left|a\right|>1</math> , show that the variance of the process <math class="inline">\left\{ \mathbf{X}_{k}\right\}</math>
  6 KB (916 words) - 08:26, 27 June 2012
• ECE600 QE 2003 August
  ...{X}_{n}\right\}</math> , has mean <math class="inline">0</math> , and has variance <math class="inline">\sigma^{2}</math> . Define <math class="inline">\mathb
  10 KB (1,608 words) - 08:31, 27 June 2012
• ECE600 QE 2006 January
  Find the variance of <math class="inline">\mathbf{Z}</math> .
  9 KB (1,560 words) - 08:30, 27 June 2012
• ECE600 QE 2006 August
  ...th> be a sequence of independent, identically distributed zero-mean, unit-variance Gaussian random variables. The sequence <math class="inline">\mathbf{X}_{n} Find the mean and variance of <math class="inline">\mathbf{X}_{n}</math> .
  14 KB (2,439 words) - 08:29, 27 June 2012
• ECE600 QE 2008 August
  Find the mean and variance of <math class="inline">\mathbf{Y}_{n}</math> .
  12 KB (1,920 words) - 08:28, 27 June 2012
• ECE 600 Exams Addition of two independent Gaussian random variables
  What kind of pdf is the pdf you determined in part (b)? What is the mean and variance of a random variable with this pdf? ...}^{2}}{\sigma_{\mathbf{X}}^{2}+\sigma_{\mathbf{N}}^{2}}\cdot y</math> and variance <math class="inline">\frac{\sigma_{\mathbf{X}}^{2}\sigma_{\mathbf{N}}^{2}}{
  7 KB (1,015 words) - 11:59, 30 November 2010
• ECE 600 Exams Addition of two jointly distributed Gaussian random variables
  ...thbf{Y}</math> has mean <math class="inline">\mu_{\mathbf{Y}}</math> and variance <math class="inline">\sigma_{\mathbf{Y}}^{2}</math> , and that the correlat Find the variance of <math class="inline">\mathbf{Z}</math> .
  3 KB (504 words) - 12:00, 30 November 2010
• ECE 600 Exams Two jointly distributed independent random variables
  ..."inline">\mathbf{Y}</math> is a Gaussian random variable with mean 0 and variance 1 . Let <math class="inline">\mathbf{U}</math> and <math class="inline">\m
  5 KB (803 words) - 12:08, 30 November 2010
• ECE 600 Exams Two jointly distributed random variables (Joint characteristic function)
  ..."inline">\mathbf{Y}</math> is a Gaussian random variable with mean 0 and variance 1 . Let <math class="inline">\mathbf{U}</math> and <math class="inline">\m
  5 KB (803 words) - 12:10, 30 November 2010
• ECE 600 Exams Geometric random variable
  (c) Find the variance of <math class="inline">\mathbf{X}</math> .
  5 KB (793 words) - 12:10, 30 November 2010
• ECE 600 Exams Mean of iid random variables
  ...ed i.i.d. random variables with mean <math class="inline">\mu</math> and variance <math class="inline">\sigma^{2}</math> . Let <math class="inline">\mathbf{Y (a) Find the variance of <math class="inline">\mathbf{Y}_{M}</math> .
  2 KB (420 words) - 11:25, 16 July 2012
• Probability Distribution
  | Variance
  6 KB (851 words) - 15:34, 23 April 2013
• Probability practice problems list
  *On expectation and/or variance of a discrete random variable
  7 KB (960 words) - 18:17, 23 February 2015
• On Principal Component Analysis
  ...ata. We define the two factors, redundancy and signal, with covariance and variance. ...e to correlate variance of the data with the strength of the signal- large variance means strong signal of data.
  6 KB (1,043 words) - 12:45, 3 March 2015
• Bayes Classification: Experiments and Notes OldKiwi
  ...in and test the system. We generated N = 10⁵ samples. Also, the variance for each feature was the same and the mean of each class feature changed de
  5 KB (772 words) - 11:05, 10 June 2013
• Lecture 16 - Parzen Window Method and K-nearest Neighbor Density Estimate OldKiwi
  This function has zero mean, H variance, an n-dimensional density, and is not compactly supported.
  10 KB (1,609 words) - 11:22, 10 June 2013
• Lecture 7 - MLE and BPE OldKiwi
  The univariate case. The variance is assumed to be known. ...be interpreted as: in making prediction for a single new observation, the variance of the estimate will have two components:
  10 KB (1,472 words) - 11:16, 10 June 2013
• Professional statement DerekRichards ECE400S12
  ...ve them perspective. The more varied my experiences became, so too did the variance in what I perceived as solutions increase. There is rarely one answer to a
  4 KB (666 words) - 12:13, 9 February 2012
• Linear combinations of independent gaussian RVs
  ...generating function of a Gaussian variable with mean <math>\mu</math> and variance <math>\sigma^2</math> where <br/>
  2 KB (453 words) - 14:19, 13 June 2013
• Lecture 19 - Nearest Neighbor Error Rates OldKiwi
  (This is equal only if variance = 0)
  6 KB (1,041 words) - 11:22, 10 June 2013
• Lecture 22 - Decision Trees and Clustering OldKiwi
  i.e. small variance in the training data can yield large variations in decision rules obtained.
  6 KB (837 words) - 11:23, 10 June 2013
• Lecture14ECE662S12
  .... More specifically, we discussed the fact that, under Gaussian noise, the variance of MLE asymptotically achieves the Cramer-Rao bound. We then warned that th
  2 KB (319 words) - 13:27, 8 March 2012
• Parametric Estimators OldKiwi
  The CRLB is the minimum variance achievable by any unbiased estimator for a parameter. ...mator that is unbiased and achieves the CRLB is referred to as the Minimum Variance Unbiased Estimator(MVUE).
  6 KB (976 words) - 13:25, 8 March 2012
• Lecture 26 - Statistical Clustering Methods OldKiwi
  which is the same as maximizing the between-cluster variance<center><math> S_{Total}=S_{W}+S_{B}</math></center> <center><math> tr(S_ ...the between-class variance is equivalent to minimizing the within-class variance.
  8 KB (1,214 words) - 11:24, 10 June 2013
• ECE PhD QE CNSIP 2001 Problem1
  ...nt, but that each have identical mean <math class="inline">\mu</math> and variance <math class="inline">\sigma^{2}</math> . Let <math class="inline">\mathbf{Y (b) Find the mean and variance of <math class="inline">\mathbf{X}\left(t\right)</math> .
  5 KB (780 words) - 01:25, 9 March 2015