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When every element of a random
vector X =(X1,X2,...,Xn) assumes the cumulative distribution function F0 and F1 with probability p and 1 - p, respectively, we have shown that the probability S0 that the first order statistic of X is originally under F0 can be expressed as . We have also shown that , where and with the support of F i (x) . Applications and implications of the results are
discussed in the performance of wideband spectrum sensing schemes.
The recent phenomena of tremendous growth in wireless communication application urge increasing need of radio spectrum, albeit it being a precious but natural resource. The recent technology under development to overview the situation is the concept of Cognitive Radio (CR). Recently the Artificial Intelligence (AI) tools are being considered for the topic. AI is the core of the cognitive engine that examines the external and internal environment parameters that leads to some postulations for QoS improvement. In this article, we propose a new Artificial Neural Network (ANN) model for detection of a spectrum hole. The model is trained with some pertinent features over a channel like SNR, channel capacity, bandwidth efficiency etc. The channel capacity status could be identified in a quantized index form . Some simulation results are presented.