We introduce new normalized fractional integral concepts on randomvariables. We also introduce the fractional coupled randomvariables. The Jensen integral inequality is generalized. Also, some fractional bounds esti...
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We introduce new normalized fractional integral concepts on randomvariables. We also introduce the fractional coupled randomvariables. The Jensen integral inequality is generalized. Also, some fractional bounds estimating the expectation and variance are delivered. At the end, some other results related to the coupled randomvariables are proved. For this work, some results of the papers [On some statistical and probability inequalities. Journal of Inequalities and Special Functions, 2016] and [Some inequalities for the expectation and variance of a randomvariable whose PDFs are absolutely continuous using a pre-Chebychev inequality. Tamkang Journal of Mathematics, 2001] are deduced as some special cases.
Let X be an arbitrary continuous random variable and Z be an independent Gaussian randomvariable with zero mean and unit variance. In this paper, we show that the third order derivative of h(X + root tZ) is nonnegati...
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ISBN:
(纸本)9781479948772
Let X be an arbitrary continuous random variable and Z be an independent Gaussian randomvariable with zero mean and unit variance. In this paper, we show that the third order derivative of h(X + root tZ) is nonnegative, which implies that the Fisher information J(X + root tZ) is convex in t. Following this result, we make two conjectures on h(X + root tZ): the first is that partial derivative(n)/partial derivative t(n) h(X + root tZ) is nonnegative in t if n is odd, and negative otherwise;the second is that log J(X + root tZ) is convex in t.
In this paper, we carry out a theoretical study of the correlation coefficients between exponential order statistics and their monotonicity properties. Then, aided by a Monte Carlo simulation study, we make some conje...
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In this paper, we carry out a theoretical study of the correlation coefficients between exponential order statistics and their monotonicity properties. Then, aided by a Monte Carlo simulation study, we make some conjectures about the correlation structure of order statistics from a larger class of distributions.
In this work, conditional entropy is used to quantify the information loss induced by passing a continuous random variable through a memoryless nonlinear input-output system. We derive an expression for the informatio...
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Li and Nadarajah [Signal Processing 127 (2016) 185-190] derived expressions for mean and variance of roundoff error for any continuous random variable. Here, we derive expressions for general moments of the roundoff e...
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Li and Nadarajah [Signal Processing 127 (2016) 185-190] derived expressions for mean and variance of roundoff error for any continuous random variable. Here, we derive expressions for general moments of the roundoff error, allowing one to study other aspects of roundoff error than just mean and variance. The expressions are specialized for 10 commonly used distributions in signal processing. Numerical studies checking the correctness of the derived expressions are given.
We propose a non-adaptive unequal error protection (UEP) querying policy based on superposition coding for the noisy 20 questions problem. In this problem, a player wishes to successively refine an estimate of the val...
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ISBN:
(纸本)9781538646595
We propose a non-adaptive unequal error protection (UEP) querying policy based on superposition coding for the noisy 20 questions problem. In this problem, a player wishes to successively refine an estimate of the value of a continuous random variable by posing binary queries and receiving noisy responses. When the queries are designed non-adaptively as a single block and the noisy responses are modeled as the outputs of a binary symmetric channel the 20 questions problem can be mapped to an equivalent problem of channel coding with UEP. A new non-adaptive querying strategy based on UEP superposition coding is introduced whose estimation error decreases with an exponential rate of convergence that is significantly better than that of the UEP repetition coding introduced by Variani et al. (2015). In fact, we show that the proposed non-adaptive UEP querying policy achieves the same order convergence rate as the adaptive policy.
We consider continuous phase modulations (CPMs) and their transmission over a typical satellite channel affected by phase noise. By modeling the phase noise as a Wiener process and adopting a simpli ed representation ...
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We consider continuous phase modulations (CPMs) and their transmission over a typical satellite channel affected by phase noise. By modeling the phase noise as a Wiener process and adopting a simpli ed representation of anM-ary CPM signal based on the principal pulses of its Laurent decomposition, we derive the MAP symbol detection strategy. Since it is not possible to derive the exact detection rule by means of a probabilistic reasoning, the framework of factor graphs (FGs) and the sumproduct algorithm is used. By pursuing the principal approach to manage continuous random variable in a FG, I.e., the canonical distribution approach, two algorithms are derived which do not require the presence of known (pilot) symbols, thanks to the intrinsic differential encoder embedded in the CPM modulator.
In this study, joint distributions of order statistics of innid continuous random variables are expressed in terms of specialized identities based on distributions of innid continuous random variables. Then, some resu...
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In this study, distribution and probability density functions of any d order statistics of innid continuous random variables are expressed. Then, some results connecting distributions of order statistics of innid rand...
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Foster and Hart propose a measure of riskiness for discrete randomvariables. Their defining equation has no solution for many common continuous distributions. We show how to extend consistently the definition of risk...
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Foster and Hart propose a measure of riskiness for discrete randomvariables. Their defining equation has no solution for many common continuous distributions. We show how to extend consistently the definition of riskiness to continuous random variables. For many continuous random variables, the risk measure is equal to the worst-case risk measure, i.e., the maximal possible loss incurred by that gamble. For many discrete gambles with a large number of values, the Foster-Hart riskiness is close to the maximal loss. We give a simple characterization of gambles whose riskiness is or is close to the maximal loss.
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