Wasfy B. Mikhael

Continuous and switched-capacitor multiphase oscillators

This paper presents novel designs of multiphase oscillators. These oscillators generate n symmetric signals, i.e., equal in amplitude and equally spaced in phase, which have a wide range of applications in communications and signal processing. First, multiphase oscillators based on active sequence discriminators (SDs) are proposed. Then multiphase oscillators based on the SD and two-integrator-loop circuits containing only capacitors, switches, and op amps are derived. In addition to the fact that these switched-capacitor oscillators (SCOs) are easily constructed in IC form using MOS technology, they are shown to possess other attractive features. The input to the switched-capacitor (SC) circuit is a clock and the output is a sampled-and-held sinusoid of a frequency that is related to the clock frequency by an arbitrarily chosen capacitor ratio. The oscillation frequency follows linearly a continuously varying clock. Thus there is no need to vary any of the oscillator components to change the oscillation frequency. Ultralow oscillation frequencies can be generated using practical component values. The harmonic content can be made very small by increasing the number of samples in each oscillation cycle. Also, the amplitude stabilization and control circuitry with excellent settling properties are presented. It is shown that the complexity of the amplitude stabilization circuitry does not increase with the number of oscillator phases in the SD oscillator design. Experimental results using both the continuous and SC realizations are given which are in agreement with the theory presented.

A fast block FIR adaptive digital filtering algorithm with individual adaptation of parameters

A general formulation for developing a fast-block least-mean-square (LMS) adaptive algorithm is presented. In this algorithm, a convergence factor is obtained that is tailored for each adaptive filter coefficient and is updated at each block iteration. These convergence factors are chosen to minimize the mean-squared error in the processed block and are easily computed from readily available signals. The algorithm is called the optimum block adaptive algorithm with individual adaptation of parameters (OBAI). It is shown that the new coefficient vector obtained from the OBAI algorithm is an estimate of the Wiener solution at each iteration. Implementation aspects of OBAI are examined and a technique is presented that eliminates matrix inversion by processing signals in overlapping blocks and applying the matrix inversion lemma. When the coefficients are updated once per input data sample, the resulting OBAI algorithm requires 7N/sup 2/-5N+9 multiplications and divisions (MAD) per iteration, where N is the number of estimated parameters. The convergence properties of OBAI are investigated and compared with several recently proposed algorithms. >

Composite operational amplifiers: Generation and finite-gain applications

A practical and effective general approach is presented for extending the useful operating frequencies and improving the performance of linear active networks realized using operational amplifiers (OAs). This is achieved by replacing each OA in the active network by a composite operational amplifier (CNOA) constructed using N OAs. The technique of generating the CNOAs for any given N is proposed. The realizations employing the CNOA are examined according to a stringent performance criterion satisfying such important properties as extended bandwidth, stability with one- and two-pole OA models, low sensitivity to the components and OA mismatch, and wide dynamic range. Several families of CNOAs, for N = 2, 3, and 4 , are shown to satisfy ,the suggested performance criterion. In this contribution, the CNOAs applications in inverting, noninverting, and differential finite-gain amplifiers are given and shown theoretically and experimentally to compare favorably with the state-of-the-art realizations using the same number of OAs. Applications of the CNOA in inverting integrator and active filter realizations are presented in a companion contribution [32].

A mixed transform approach for efficient compression of medical images

A novel technique is presented to compress medical data employing two or more mutually nonorthogonal transforms. Both lossy and lossless compression implementations are considered. The signal is first resolved into subsignals such that each subsignal is compactly represented in a particular transform domain. An efficient lossy representation of the signal is achieved by superimposing the dominant coefficients corresponding to each subsignal. The residual error, which is the difference between the original signal and the reconstructed signal is properly formulated. Adaptive algorithms in conjunction with an optimization strategy are developed to minimize this error. Both two-dimensional (2-D) and three-dimensional (3-D) approaches for the technique are developed. It is shown that for a given number of retained coefficients, the discrete cosine transform (DCT)-Walsh mixed transform representation yields a more compact representation than using DCT or Walsh alone. This lossy technique is further extended for the lossless case. The coefficients are quantized and the signal is reconstructed. The resulting reconstructed signal samples are rounded to the nearest integer and the modified residual error is computed. This error is transmitted employing a lossless technique such as the Huffman coding. It is shown that for a given number of retained coefficients, the mixed transforms again produces the smaller rms-modified residual error. The first-order entropy of the error is also smaller for the mixed-transforms technique than for the DCT, thus resulting in smaller length Huffman codes.

Region based variable quantization for JPEG image compression

Introduces concepts that optimize image compression ratio by utilizing the information about a signals properties and their uses. This additional information about the image is used to achieve further gains in image compression. The techniques developed in this work are on the ubiquitous JPEG still image compression standard [IS094] for compression of continuous tone grayscale and color images. This paper is based on a region based variable quantization JPEG software codec that was developed tested and compared with other image compression techniques. The application, named JPEGTool, has a graphical user interface (GUI) and runs under Microsoft Windows (R) 95. This paper discusses briefly the standard JPEG implementation and software extensions to the standard. region selection techniques and algorithms that complement variable quantization techniques are presented in addition to a brief discussion on the theory and implementation of variable quantization schemes. The paper includes a presentation of generalized criteria for image compression performance and specific results obtained with JPEGTool.

A survey of mixed transform techniques for speech and image coding

The goal of transform based coding is to build a representation of a signal using the smallest number of weighted basis functions possible, while maintaining the ability to reconstruct the signal with adequate fidelity. Mixed transform techniques, which employ subsets of non-orthogonal basis functions chosen from two or more transform domains, have been shown to consistently yield more efficient signal representations than those based on one transform. This paper provides a survey of mixed transform techniques, also known as multitransforms or mixed basis representations, which have been developed for speech and image coding.

Adaptive Digital Controller and Design Considerations for a Variable Switching Frequency Voltage Regulator

An auto-tuning adaptive digital controller with maximum efficiency point tracking to optimize dc-dc converter switching frequency is presented in this paper. The adaptive-frequency-optimization (AFO) controller adjusts the dc-dc converter switching frequency while tracking the converter minimum input power (maximum efficiency) point under variable operation conditions of the power converter. The AFO digital controller continuously finds the optimum switching frequency that will result in minimum total power loss while converter parameters and conditions vary. Moreover, the presented controller addresses the issues that are associated with implementing variable switching frequency in digital controllers, including limit cycle oscillation and possible performance degradation, by using a dynamic algorithm to maintain converter system stability under variable switching frequency operation. In this paper, the proposed controller is discussed, analyzed, and its digital control algorithms and experimental results are presented.

Efficient restoration of space-variant blurs from physical optics by sectioning with modified Wiener filtering

Abstract Digital images blurred by space-variant point-spread functions of uncorrected physical optics may be efficiently restored using Wiener filtering on overlapping subimage frames. Frame size must be tailored to accommodate the displacement-dependent spreading and shifting of physical point-spread functions at large field angles to prevent circular convolution edge effects from corrupting the frames central section. We define the section as the nonoverlapping subframe used to construct the composite full-image restoration. Otherwise, if the frame is too small, edge-effect errors may extend into the section, inducing artifacts in the composite restoration. Conversely, if the frame is too large, total restoration processing will be greater than necessary. By adjusting frame size with field displacement, we demonstrate the effective restoration of images blurred by a laboratory-grade spherical lens. Blurred images are simulated and then restored with a modified Wiener filter. Mean-square-error and restoration improvement are reported as a function of field angle and criteria are developed for frame and section size selection.

Energy-Based Split Vector Quantizer Employing Signal Representation in Multiple Transform Domains

Mikhael, W., and Krishnan, V., Energy-Based Split Vector Quantizer Employing Signal Representation in Multiple Transform Domains, Digital Signal Processing11 (2001) 359?370Vector quantization schemes are widely used for waveform coding of one- and multidimensional signals. In this contribution, a novel energy-based, split vector quantization technique is presented, which represents digital signals efficiently as measured by the number of bits per sample for a predetermined signal reconstruction quality. In this approach, each signal vector is projected into multiple transform domains. In the learning mode, for a given transform domain representation, the transformed vector is split into subvectors (subbands) of equal average energy estimated from the transformed training vector ensemble. An equal number of bits is assigned to each subvector. A codebook is then designed for each equal energy subband of each transform domain representation. In the running mode, the coder selects codes from the domain that best represents the signal vector. The proposed multiple transform, split vector quantizer is developed and its performance is evaluated for both single-stage and multistage implementations. Several single transform vector quantizers for waveform coding exist, some of which employ energy-based bit allocation. Sample results using one-dimensional speech signals confirm the superior performance of the proposed scheme over existing single transform vector quantizers for waveform coding.

Two-dimensional variable step-size sequential adaptive gradient algorithms with applications

The optimality criterion governing the choice of the convergence factor for the 2-D sequential adaptive gradient algorithms is developed. Two 2-D variable step-size sequential algorithms satisfying the proposed optimality constraint are derived and investigated. These are the 2-D individual adaptation (TDIA) algorithm and the 2-D homogeneous adaptation (TDHA) algorithm. The TDIA algorithm uses 2-D optimal convergence factors tailored for each 2-D adaptive filter coefficient at each iteration. The TDHA algorithm uses the same convergence factor for all the filter coefficients, but the convergence factor is optimally updated at each iteration. Neither algorithm requires any a priori knowledge about the statistics of the system signals. In addition, the convergence factors are easily obtained from readily available signals without any differentiation or matrix inversions. The convergence characteristics and adaptation accuracy are greatly improved at the expense of a modest increase in computational complexity. >