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Cognitive radio is an exciting emerging technology that has the ability to deal with the requirements of the frequency spectrum. CR allows usage of the frequency spectrum more efficiently. CR systems built in this book based on SDR to distinguish between signal and noise. The heavily used generated modulated signals: FSK, PSK and QAM are generated and used in this work. These systems consist of feature extraction and decision stages. Both instantaneous features and statistical features are used in this work. Neural networks are also used in the detection process. Six detection systems are proposed in this work. Most of these systems are based on CFAR The assessment of results showed that the proposed CR detection systems provide detection probability higher than the other proposed systems of the published papers. A novel technique is presented to estimate SNR for CR based on statistical features by calculation the cumulants for signals. This is an indirect method for SNR measurements. Thresholds decision and NVG-RAM detectors at intermediate frequency of 20MHz which are based on statistical features are implemented by FPGA Spartan-3A DSP 3400A due to their higher performance.