Mohammad Bari

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The objectives of this project were to evaluate the effect of alkanols and cyclodextrins on the phase behavior of an isopropyl myristate microemulsion system and to examine the solubility of model drugs. Triangular phase diagrams were developed for the microemulsion systems using the water titration method, and the solubility values of progesterone and(More)
In this paper we propose a feature to distinguish frequency from amplitude-phase digital modulations. We compare the performance of the feature where every symbol is sampled more than once to that where every symbol is sampled only once. The feature is based on the product of two consecutive signal values and on time averaging of the imaginary part of the(More)
In this paper we propose simple and robust features to distinguish continuous-phase frequency shift keying from quadrature amplitude and phase shift keying modulations. Robustness is tested in the presence of SNR estimation offset, block and correlated fast fading, lack of symbol and sampling synchronization, and carrier offset. The features are based on(More)
In this letter we propose simple and robust features to distinguish continuous-phase frequency shift keying from quadrature amplitude modulation and phase shift keying modulations. The features are based on sample mean and sample variance of the imaginary part of the product of two consecutive complex signal values. Root raised cosine pulses are used to(More)
—This work presents sample mean and sample variance based features that distinguish continuous phase FSK from QAM and PSK modulations. Root raised cosine pulses are used for signal generation. Support vector machines are employed for signals separation. They are trained for only one value of SNR and used to classify the signals from a wide range of SNR. A(More)
In this paper we study approximate entropy as the feature to distinguish within the class of L-ary continuous-time FSK in the presence of correlated fast fading and additive white Gaussian noise. Support vector machines are employed to distinguish the signals. One benefit of using support vector machines is that they require very few realizations for(More)