Mohamed El-Sharkawy

Adaptive stochastic filters with no strict positive real condition

A new adaptive stochastic filter structure is introduced which avoids the strict passivity test used as a sufficient condition for convergence required by existing adaptive schemes. The proposed algorithm consists of three stages. In the first stage, an autoregressive model is fitted and the residue obtained is used as an estimate of the noise. In the second stage, an autoregressive recursive moving average model is fitted using the residual of the first stage. A modified residual is then filtered using a parameter δ and the model obtained from the second stage to generate an improved estimate of the noise. In the third stage, this improved estimate of the noise is used to obtain a better autoregressive moving average model. It is shown that the proposed algorithm will also reduce the bias in the estimated parameters. The simulation results given show that the proposed filter compares favorably to the algorithm introduced by Mayne and Clark and also Landau. This filter is then applied to the adaptive line enhancement, sinusoidal detection, and adaptive spectral estimation problems to illustrate its usefulness.

Wide-Band Cooperative Compressive Spectrum Sensing for Cognitive Radio Systems Using Distributed Sensing Matrix

In this paper, cooperative compressive spectrum sensing is considered to enable accurate sensing of the wide-band spectrum. The proposed algorithm is based on compressive sensing theory and aims to reduce the hardware complexity of the cognitive radio receiver by distributing the sensing work among groups of sensing nodes. The proposed algorithm classifies the cooperated sensing nodes into different sensing groups depending on the quality of the reporting channel between the sensing node and the fusion center (FC). To sense the wide- band analog signal and take a global decision about spectrum occupancy, each node uses its local sensing matrix, which is assigned to its sensing group and a part of a global sensing matrix at the FC. The size of the local sensing matrix of each sensing node,and consequently the contribution of this node in the overall measurement vector, depends on its sensing group. The FC classifies and rearranges the compressed data to formulate one global measurement vector which is used with a global sensing matrix to estimate the wide-band signal spectrum. The receiver operation characteristics (ROC) of the overall spectrum sensing system show that the proposed receiver provides more protection to primary users (higher detection probability) at the same secondary user throughput (probability of false alarm).

A fast recursive pruned DCT for image compression applications

This paper presents a recursive algorithm for computing the pruned DCT with a structure that allows the generation of the next higher order pruned DCT from two identical lower order pruned DCTs. The implementation of the proposed algorithm does not require bit-reversal shuffling, coefficient inversions or divisions. To illustrate the usefulness of the proposed recursive pruned DCT algorithm, we utilizes it to compress images using the JPEG algorithm. The proposed pruned DCT algorithm improves the compression ratio and reduces both the complexity and execution time of the modified JPEG algorithm.

Optimized bases compressive spectrum sensing for wideband cognitive radio

Designing efficient spectrum sensing techniques with low power consumption is crucial for the success of cognitive radio (CR). This is particularly challenging when sensing a wideband spectrum due to the high sampling rate required. Compressive sensing (CS) theory states that a signal can be measured at a rate significantly lower than the Nyquist rate and consequently reconstructed from the measurements using an optimization process. The minimum number of measurements required for reliable reconstruction of the sampled signal depends on the sparsity of the measured signal. To improve the performance of compressive spectrum sensing, we optimize the sparsifying bases used to represent the measured spectrum. Entropy-based best basis selection algorithm of Coifman and Wickerhauser (CW) is deployed to find the optimum basis. Our simulation results show that the proposed compressive sampling technique can improve the spectrum estimation accuracy and enhance the detection and false-alarm probabilities of the CR system at the same sampling rates.

Analysis and control of hybrid-electric vehicles with individual wheel brushless traction motors

Focuses on design, development, demonstration and implementation of a highly efficient drive-by-wire direct-wheel-drive transmissionless propulsion systems for light, medium, and heavy vehicles. The problems to be solved are extremely challenging because a number of longstanding problems in nonlinear analysis and control, optimization and design, manufacturing, technology developments and technology transfer have to be solved in order to develop high-performance diesel-electric powertrains to be deployed in new generations of cars, pickups, trucks, buses and other vehicles. The major emphases are placed on improving fuel economy, reducing emission, attaining the desired vehicle performance, increasing reliability and ruggedness, and decreasing cost and maintenance. Novel control algorithms and innovative methods in design of optimal energy management systems are studied. These optimal energy management systems are needed to attain motion control, diagnostics, and decision making. The decision making and control algorithms were integrated in the optimal energy management systems to control diesel-electric drivetrains. The high-level simulation architecture using advanced software environments (MATLAB and SIMULINK) is developed to perform comprehensive analysis of hybrid-electric vehicles (HEVs). Comprehensive analysis of the basic components of diesel-electric drivetrains are performed. The results of evaluations of diesel-electric drives (diesel-starter/generator-power converters-traction motors) and nonlinear analysis of HEVs with optimal energy management systems are presented.

A constructive algorithm for stabilization of nonlinear neutral time-delayed systems occurring in bioengineering

A criterion is given for the stabilization of the trivial solutions solution of a nonlinear functional differential equation of neutral type occurring in bioengineering under the assumptions of continuity and boundedness of the coefficients. The criterion is a condition on the roots of a certain ‘quasi-polynomial’, i.e. a polynomial in a variable and exponential of that variable. The derivation is based on a constructive algorithm which generates a stabilizing control. The method is illustrated by the construction of stabilizing control for a smooth per suit eye movement system. It is shown that for the synthesis of required control function it is unnecessary in a number of cases to solve the corresponding Riccati matrix equation; rather, it is sufficient to find the roots of a certain ‘quasi-polynomial’, i.e. a polynomial in a variable and exponential of that variable. The model of the smooth pursuit eye movement system can be mathematically described by a set of nonlinear, neutral, functional differenti...

High Speed Search Algorithms for Block-Based Motion Estimation Video Compression

The enormous computations associated with motion estimation prevent software implementations from running in real time. A hardware implementation to achieve real time video compression was demonstrated utilizing mentor graphics tools. Several block-matching criteria and architectures were developed to improve the hardware efficiency and computational speed of block-matching VLSI chips. The VHDL code for block-based motion estimation was designed using high speed arithmetic units. As the complexity of motion estimation is greatly influenced by the search algorithm and search range, the design focuses mainly on the high throughput rate and scalability for increased search ranges. The design was simulated for different image sizes at different clock frequencies with varying block sizes and search areas. The paper details the search algorithms and simulation results in order to achieve high speed hardware processing. With a clock frequency of 400MHz, the estimated time for motion estimation for QCIF and CIF sequences shows the feasibility for real-time video-codec

Analysis and design of fuzzy control systems with random delays using invariant cones

In this paper, a class of fuzzy stochastic control systems with random delays is examined. The fuzzy rule base used consists of a collection of r fuzzy IF-THEN rules defined as a function of the conditional variable. The method of theory of invariant cones is used to design a class of local fuzzy control law. A verifiable sufficient condition for stochastic stability of the fuzzy stochastic delay differential equation is given.

A Fast 8 × 8 Pruned DCT Algorithm

Abstract El-Sharkawy, M., and Eshmawy, W., A Fast 8 × 8 Pruned DCT Algorithm, Digital Signal Processing 6 (1996), 145–154. A new algorithm that computes the 8 × 8 pruned Discrete Cosine Transform (DCT) using the vector–radix approach is introduced. The vector–radix approach decomposes the 8 × 8 pruned DCT into four 4 × 4 pruned DCTs. The 4 × 4 pruned DCT is then decomposed into four one-dimensional pruned DCTs. The number of points that need to be calculated from each one-dimensional DCT depends on the allowed amount of pruning. The proposed algorithm does not require any bit reversal operations. To illustrate the usefulness of the proposed pruned DCT algorithm, we utilize it to compress images using a Joint Photographic Experts Group (JPEG) algorithm. The proposed 8 × 8 pruned DCT algorithm improves the compression ratio and reduces both the complexity and execution time of the modified JPEG algorithm.

Blocking artifacts reduction for image compression algorithms

In this paper, a new algorithm is proposed to improve the performance of the existing JPEG image compression algorithm. The algorithm proposes a recursive pruned discrete cosine transform (DCT) to reduce the bit rate and two different methods to reduce the image artifacts arising at these lower bit rates. The recursive algorithm computes the pruned DCT using a structure that allows the generation of higher order pruned DCT from two identical, lower order pruned DCTs. A variance dependent pruning method determines the pruning based on the statistical properties of the image block. A linear filtering method performs low pass filtering on the block boundaries for smoothing the discontinuities.