Said E. El-Khamy

Bio: Said E. El-Khamy is an academic researcher from Alexandria University. The author has contributed to research in topics: Wavelet & Fading. The author has an hindex of 22, co-authored 276 publications receiving 1736 citations. Previous affiliations of Said E. El-Khamy include University of Massachusetts Amherst & King Abdulaziz University.

New trends in wireless multimedia communications based on chaos and fractals

Abstract: The aim of this paper is to emphasize on the many possible applications of chaos and fractals in wireless multimedia communication systems and to describe the nature and properties of chaotic and fractal signals which make them suitable for solving many of the limitations of wireless channels. Among the considered applications are: (i) the use of fractals in the design of wideband and multiband antennas; (ii) the design of chaotic and fractal spreading codes for spread spectrum and CDMA systems to result in improved performance, increase the capacity and provide more security to the system; (iii) chaotic modulation techniques which provide improved performance in interference environments as well as improved security features; (iv) chaos cryptosystems; (v) fractal modulation techniques which allow multirate transmission and increased reliability; (vi) fractal based compression and watermarking techniques.

A modified fuzzy Sobel edge detector

Abstract: A modified fuzzy Sobel method for edge detection and enhancement is proposed. This method is a modification of the fuzzy Sobel method proposed by Kuo, Lee and Liu see (IEEE Conference on Fuzzy Systems, p.1069-74, 1997). The proposed method overcomes the drawbacks of the conventional gradient methods for edge detection such as Prewitt and Sobel methods. It automatically obtains four threshold values, and apply fuzzy reasoning for edge enhancement. The edges extracted by this method are very clear and provides better representation for image edges and object contours.

Efficient multiple-access communications using multi-user chirp modulation signals

Abstract: In this paper, we present a novel technique for multi-user communication system utilizing binary chirp modulated (CM) signals. This suggested technique is motivated by the inherent interference rejection capability of such spread-spectrum type system, specially in circumstances where immunity against Doppler shift and fading due to multipath propagation are important. The used chirp signals are selected such that they all have the same power as well as the same bandwidth. Closed form expressions, as well as approximate analytical expressions, for the cross-coherence functions between the different forms of considered chirp signals are derived. The performance of a suggested coherent receiver structure is investigated and the corresponding error rates are presented. The results show that the proposed multiuser chirp signaling technique is efficient and promising as a multiple-access technique.

Improved wideband spectrum sensing techniques using wavelet-based edge detection for cognitive radio

Abstract: Cognitive Radio networks demand a fast and accurate wideband spectrum sensing in order to operate successfully and achieve efficient spectrum utilization. The wavelet transform, being a multiresolution analysis tool, has been proposed to process the target spectrum to achieve both speed and accuracy. In this paper, we propose an improved algorithm, based on the characterization of spectrum singularities from their wavelet transform multiscale information for wideband spectrum sensing. The proposed algorithm performs better than the existing ones at medium-to-high noise power. In addition, modifications are introduced to the wavelet transform multiscale sum algorithm to improve its performance. We also show that the Gaussian wavelet is the best wavelet basis function for this spectrum sensing approach. Finally, new performance measures are introduced and evaluated to provide accurate assessment of wideband spectrum sensing techniques.

An overview of fractal antenna engineering research

Abstract: Recent efforts by several researchers around the world to combine fractal geometry with electromagnetic theory have led to a plethora of new and innovative antenna designs. In this report, we provide a comprehensive overview of recent developments in the rapidly growing field of fractal antenna engineering. Fractal antenna engineering research has been primarily focused in two areas: the first deals with the analysis and design of fractal antenna elements, and the second concerns the application of fractal concepts to the design of antenna arrays. Fractals have no characteristic size, and are generally composed of many copies of themselves at different scales. These unique properties of fractals have been exploited in order to develop a new class of antenna-element designs that are multi-band and/or compact in size. On the other hand, fractal arrays are a subset of thinned arrays, and have been shown to possess several highly desirable properties, including multi-band performance, low sidelobe levels, and the ability to develop rapid beamforming algorithms based on the recursive nature of fractals. Fractal elements and arrays are also ideal candidates for use in reconfigurable systems. Finally, we provide a brief summary of recent work in the related area of fractal frequency-selective surfaces.

Linear transmit processing in MIMO communications systems

Abstract: We examine and compare the different types of linear transmit processing for multiple input, multiple output systems, where we assume that the receive filter is independent of the transmit filter contrary to the joint optimization of transmit and receive filters. We can identify three filter types similar to receive processing: the transmit matched filter, the transmit zero-forcing filter, and the transmit Wiener filter. We show that the transmit filters are based on similar optimizations as the respective receive filters with an additional constraint for the transmit power. Moreover, the transmit Wiener filter has similar convergence properties as the receive Wiener filter, i.e., it converges to the matched filter and the zero-forcing filter for low and high signal-to-noise ratio, respectively. We give closed-form solutions for all transmit filters and present the fundamental result that their mean-square errors are equal to the errors of the respective receive filters, if the information symbols and the additive noise are uncorrelated. However, our simulations reveal that the bit-error ratio results of the transmit filters differ from the results for the respective receive filters.

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

Abstract: Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed