Omar M. Abdul-Latif

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Support vector machine (SVM) is a statistical learning tool developed to a more complex concept of structural risk minimization. SVM is playing an increasing role in applications to detection problems in statistical signal processing and communication systems. In this paper, SVM is applied to the detection of root-mean-square-gain combining (RMSGC)(More)
This paper considers a new location scheme for ultra wideband (UWB) positioning system. The newly adopted scheme combines the time difference of arrival (TDOA) and the angle of arrival (AOA) positioning techniques in order to enhance the accuracy of the positioning system compared to the classical technique (TDOA). The new technique is simulated in a sports(More)
In this paper, we study FPGA implementation of a novel receiver diversity combining technique, RMSGC for wireless transmission over fading channels in SIMO systems. Prior published results using ML-detected RMSGC diversity signal driven by BPSK showed superior bit error rate performance to classical diversity combining schemes. RMSGC was shown to be(More)
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