Muhammad Waqar Aslam

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Diabetes is one of the common and rapidly increasing diseases in the world. It is a major health problem in most of the countries. Due to its importance, the need for automated detection of this disease is increasing. The method proposed here uses genetic programming (GP) and a variation of genetic programming called GP with comparative partner selection(More)
With the classification performance and computational complexity in mind, we propose a new optimized distribution sampling test (ODST) classifier for automatic classification of M-QAM signals. In ODST, signal cumulative distributions are sampled at pre-established locations. The actual sampling process is transformed into simple counting task for reduced(More)
Automatic modulation classification (AMC) is used to identify automatically the modulation types of transmitted signals using the received data samples in the presence of noise. It is a very important process for a receiver that has no, or limited, knowledge of signals received. It is an intermediate step between signal detection and demodulation and has(More)
In this paper, we explore new Adapted Geometric Semantic (AGS) operators in the case where Genetic programming (GP) is used as a feature generator for signal classification. Also to control the computational complexity, a devolution scheme is introduced to reduce the solution complexity without any significant impact on their fitness. Fisher's criterion is(More)
Automatic modulation classification is an intrinsically interesting problem with various civil and military applications. A generalized digital modulation classification algorithm has been developed and presented in this paper. The proposed algorithm uses Genetic Programming (GP) with K-Nearest Neighbor (K-NN). The algorithm is used to identify BPSK, QPSK,(More)
In this paper, we propose distribution based binary discriminative features and a novel feature enhancement process for automatic modulation classification. The new features exploit the signal distribution mismatch between two modulations. Signal distributions on I-Q segments, amplitude and phase, are considered to produce a comprehensive feature set for(More)
Automatic modulation recognition has seen increasing demand in recent years. It has found many applications in wireless communications, including both civilian and military applications. It is a scheme to identify automatically the modulation type of received signal by observing data samples of received signals in the presence of noise. In this paper a(More)