Realization of Analog Wavelet Filter using Hybrid Genetic Algorithm for On-line Epileptic Event Detection

© 2020 The Author(s). This open access work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/.As the evolution of traditional electroencephalogram (EEG) monitoring unit for epilepsy diagnosis, wearable ambulatory EEG (WAEEG) system transmits EEG data wirelessly, and can be made miniaturized, discrete and social acceptable. To prolong the battery lifetime, analog wavelet filter is used for epileptic event detection in WAEEG system to achieve on-line data reduction. For mapping continuous wavelet transform to analog filter implementation with low-power consumption and high approximation accuracy, this paper proposes a novel approximation method to construct the wavelet base in analog domain, in which the approximation process in frequency domain is considered as an optimization problem by building a mathematical model with only one term in the numerator. The hybrid genetic algorithm consisting of genetic algorithm and quasi-Newton method is employed to find the globally optimum solution, taking required stability into account. Experiment results show that the proposed method can give a stable analog wavelet base with simple structure and higher approximation accuracy compared with existing method, leading to a better spike detection accuracy. The fourth-order Marr wavelet filter is designed as an example using Gm-C filter structure based on LC ladder simulation, whose power consumption is only 33.4 pW at 2.1Hz. Simulation results show that the design method can be used to facilitate low power and small volume implementation of on-line epileptic event detector.Peer reviewe

Extended frequency-band-decomposition sigma–delta A/D converter

Parallelism can be used to increase the bandwidths of ADC converters based on sigma–delta modulators. Each modulator converts a part of the input signal band and is followed by a digital filter. Unfortunately, solutions using bandpass sigma–delta modulators are very sensitive to the position of the modulators' central frequencies. This paper shows the feasibility of a frequency-band-decomposition (FBD) ADC using continuous time bandpass sigma–delta modulators, even in the case of large analog mismatches. The major benefit of such a solution, called extended-frequency-band-decomposition (EFBD) is its low sensitivity to analog parameters. For example, a relative error in the central frequencies of 4% can be accepted without significant degradation in the performance (other published FBD ADCs require a precision of the central frequencies better than 0.1%). This paper will focus on the performance which can be reached with this system, and the architecture of the digital part. The quantization of coefficients and operators will be addressed. It will be shown that a 14 bit resolution can be theoretically reached using 10 sixth-order bandpass modulators at a sampling frequency of 800 MHz which results in a bandwidth of 80 MHz centered around 200 MHz (the resolution depends on the effective quality factor of the filters of the analog modulators)

The design and implementation of a wideband digital radio receiver

Historically radio has been implemented using largely analogue circuitry. Improvements in mixed signal and digital signal processing technology are rapidly leading towards a largely digital approach, with down-conversion and filtering moving to the digital signal processing domain. Advantages of this technology include increased performance and functionality, as well as reduced cost. Wideband receivers place the heaviest demands on both mixed signal and digital signal processing technology, requiring high spurious free dynamic range (SFDR) and signal processing bandwidths. This dissertation investigates the extent to which current digital technology is able to meet these demands and compete with the proven architectures of analogue receivers. A scalable generalised digital radio receiver capable of operating in the HF and VHF bands was designed, implemented and tested, yielding instantaneous bandwidths in excess of 10 MHz with a spurious-free dynamic range exceeding 80 decibels below carrier (dBc). The results achieved reflect favourably on the digital receiver architecture. While the necessity for minimal analogue circuitry will possibly always exist, digital radio architectures are currently able to compete with analogue counterparts. The digital receiver is simple to manufacture, based on the use of largely commercial off-the-shelf (COTS) components, and exhibits extreme flexibility and high performance when compared with comparably priced analogue receivers

Unified Large And Small Signal State-space Based Modeling And Symbolic Simulation For Pwm Converters

In this Dissertation, which concentrates on discrete modeling for control purposes of DC/DC converters and simulation through symbolic techniques. A Unified Discrete State-Space Model for power converters in CCM is presented. Two main approaches to arriving at the discrete model are used. The first approach involves an impulse function approximation of the duty cycle modulation of the converter switches, and this approach results in a small signal discrete model. The Second approach is direct and does not involve any approximation of the modulation, this approach yields both a large signal nonlinear discrete model and a linear small signal model. Harmonic analysis of the converter\u27s states at steady-state is done for steady-state waveform acquisition, which increases the accuracy of the model especially for finding the control to inductor current frequency response. Also the harmonic Analysis technique is used to both obtain the response of the converter to a load transient and to finding the optimal duty cycle response that minimizes the disturbance. Finally the Discrete model is verified for the Half-Bridge DC/DC topology for its three main control schemes (Asymmetric, Symmetric, DCS). A GUI platform in MATLAB is presented as a wrapper that utilizes the models and analysis presented in this thesis. Symbolic simulation techniques are developed in general manner for linear piecewise circuits and then through State-Space formalism specialized for DC/DC converters. A general symbolic solver programmed in JAVA that implements said techniques is presented

Measurements, Models, Systems and Design

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Engineering Education and Research Using MATLAB

MATLAB is a software package used primarily in the field of engineering for signal processing, numerical data analysis, modeling, programming, simulation, and computer graphic visualization. In the last few years, it has become widely accepted as an efficient tool, and, therefore, its use has significantly increased in scientific communities and academic institutions. This book consists of 20 chapters presenting research works using MATLAB tools. Chapters include techniques for programming and developing Graphical User Interfaces (GUIs), dynamic systems, electric machines, signal and image processing, power electronics, mixed signal circuits, genetic programming, digital watermarking, control systems, time-series regression modeling, and artificial neural networks

A study of pilot modeling in multi-controller tasks

A modeling approach, which utilizes a matrix of transfer functions to describe the human pilot in multiple input, multiple output control situations, is studied. The approach used was to extend a well established scalar Wiener-Hopf minimization technique to the matrix case and then study, via a series of experiments, the data requirements when only finite record lengths are available. One of these experiments was a two-controller roll tracking experiment designed to force the pilot to use rudder in order to coordinate and reduce the effects of aileron yaw. One model was computed for the case where the signals used to generate the spectral matrix are error and bank angle while another model was computed for the case where error and yaw angle are the inputs. Several anomalies were observed to be present in the experimental data. These are defined by the descriptive terms roll up, break up, and roll down. Due to these algorithm induced anomalies, the frequency band over which reliable estimates of power spectra can be achieved is considerably less than predicted by the sampling theorem

Design and Implementation of Internal Model Based Controllers for DC/ AC Power Converters

The aim of this thesis is to design and implement an advanced control system for a working three-phase DC to AC power converter. Compared to' the traditional PI controller used widely in industry, the new voltage controller can track the reference voltage with improved accuracy and efficiency in the presence of different kind of local loads, and also works well in the single phase voltage control. This voltage controller is combined with a power controller to yield a complete controller. An important aspect of this work is the hardware implementation of the whole system. Main parts ofthis thesis are: ???????? 1. Review ofH-infinity and repetitive control techniques and their applications in power converters. 2. Design of a new voltage controller to eliminate the DC component in the output voltages, and taking into account the practical issues such as the processing delay due to the digital signal processor (DSP) implementation. 3. Modelling and simulation of the converter system incorporating different control techniques and with different kinds of loads. 4. Hardware implementation and the two-processor controller. The parallel communication between the DSPs. 5. The main problems encountered in???????????????????? hardware implementation and programming. The software used to initialize DSPs, implement the discretetime voltage controller and other functions such ~ generations of space vector pulse width modulation (SVPWM) signals, circuit protections, analog to digital (AD) cOl)versions, data transmission, etc. 6. Experimental results the under circumstances of no load connected to the converter, pure three-phase resistive loads, three-phase unbalanced resistive' loads and the series resistor-inductor loads. /Imperial Users onl

Sampling from a system-theoretic viewpoint

This paper studies a system-theoretic approach to the problem of reconstructing an analog signal from its samples. The idea, borrowed from earlier treatments in the control literature, is to address the problem as a hybrid model-matching problem in which performance is measured by system norms. \ud \ud The paper is split into three parts. In Part I we present the paradigm and revise the lifting technique, which is our main technical tool. In Part II optimal samplers and holds are designed for various analog signal reconstruction problems. In some cases one component is fixed while the remaining are designed, in other cases all three components are designed simultaneously. No causality requirements are imposed in Part II, which allows to use frequency domain arguments, in particular the lifted frequency response as introduced in Part I. In Part III the main emphasis is placed on a systematic incorporation of causality constraints into the optimal design of reconstructors. We consider reconstruction problems, in which the sampling (acquisition) device is given and the performance is measured by the $L^2$-norm of the reconstruction error. The problem is solved under the constraint that the optimal reconstructor is $l$-causal for a given $l\geq 0,$ i.e., that its impulse response is zero in the time interval $(-\infty,-l h),$ where $h$ is the sampling period. We derive a closed-form state-space solution of the problem, which is based on the spectral factorization of a rational transfer function

Optimal design of discrete-time delta sigma modulators

In this thesis, optimal signal transfer functions (STFs) and noise transfer functions (NTFs) for discrete time delta sigma (ΔΣ) modulators are determined. For a given oversampling rate (OSR), these STFs and NTFs are optimized with respect to a weighted combination of the ΔΣ modulator\u27s signal-to-noise ratio (SNR) and dynamic range (DR). This optimization problem is solved using a novel hybrid orthogonal genetic (HOG) algorithm that uses customized genetic operators to improve algorithm performance and accuracy when applied to multimodal, non-differentiable performance surfaces. To generate optimal system functions, the HOG algorithm is implemented as a constrained global optimizer to minimize cost functions which represent approximations of the system functions