Prasad Ponnapalli

Manchester Metropolitan University

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Nader Anani

University of Wolverhampton

Mahmoud Al‐Qutayri

Khalifa University of Science and Technology

Saleh R. Al‐Araji

Khalifa University of Science and Technology

Omar Al-Kharji Al-Ali

National Telecommunication Regulatory Authority

Tim Collins

University of Birmingham

Abdel–Razzak Natsheh

An-Najah National University

Dalil Benchebra

Manchester Metropolitan University

M. Thomson

Heriot-Watt University

Atef El-kholy

Manchester University NHS Foundation Trust

Omar A. Al-Kharji

Manchester Metropolitan University

Cooperative Institutions

Manchester Metropolitan University

Heriot-Watt University

University of Manchester

Manchester University

University of Sheffield

Lancaster University

University of Sharjah

Zhengzhou University

University of Southampton

Khalifa University of Science and Technology

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Automated Tool for Diagnosis of Sinus Analysis CT Scans

Springer eBooks (2007)

Abdel–Razzak Natsheh Prasad Ponnapalli Nader Anani Atef El-kholy

Sinus (botany)

10.1007/978-1-84800-086-5_10

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Citations (4)

G.A. Optimisation of PID Controllers — Optimal Fitness Functions

D. Drabble Prasad Ponnapalli M. Thomson

Genetic Algorithms (GAs) have been in many cases successfully applied to a wide variety of optimisation problems. The work described here focuses on the application of genetic algorithms to the optimisation of linear & non-linear PID controllers. The techniques used here are based around the formulation of a suitable objective function, which, as part of the GA evaluates the fitness of a given PID parameter set. The proposed objective function is based directly on performance criteria specified in terms of the rise time, settling time and peak overshoot of a physical system. The functions are evaluated via a set of trials on a range of systems with varying dynamics and the success rate determined by comparison with sets of target step response characteristics. The results show that the objective function is more robust than ISE based methods in the optimisation of multiple step response objectives, having a low deviation from the target across the range of parameters (rise time, settling time & peak overshoot).

Settling time

Overshoot (microwave communication)

10.1007/978-3-7908-1829-1_22

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A formal selection and pruning algorithm for feedforward artificial neural network optimization

IEEE Transactions on Neural Networks (1999)

Prasad Ponnapalli K.C. Ho M. Thomson

A formal selection and pruning technique based on the concept of local relative sensitivity index is proposed for feedforward neural networks. The mechanism of backpropagation training algorithm is revisited and the theoretical foundation of the improved selection and pruning technique is presented. This technique is based on parallel pruning of weights which are relatively redundant in a subgroup of a feedforward neural network. Comparative studies with a similar technique proposed in the literature show that the improved technique provides better pruning results in terms of reduction of model residues, improvement of generalization capability and reduction of network complexity. The effectiveness of the improved technique is demonstrated in developing neural network models of a number of nonlinear systems including three bit parity problem, Van der Pol equation, a chemical processes and two nonlinear discrete-time systems using the backpropagation training algorithm with adaptive learning rate.

Feedforward neural network

Pruning

Feed forward

10.1109/72.774273

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Citations (53)

Introduction to expert systems. 2nd edn, P. Jackson, Addison‐Wesley, Wokingham, 1990, ISBN 0‐201‐17578‐9, xi + 526pp, £21.95

International Journal of Adaptive Control and Signal Processing (1992)

Prasad Ponnapalli

to GRAFCET (a graphical language).In addition,

Prasad

10.1002/acs.4480060107

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Prediction of line current harmonics in an AC-DC converter using neural networks

Nader Anani Dalil Benchebra Prasad Ponnapalli Abdel–Razzak Natsheh

A circuit topology for an AC-DC single-phase single-stage half-controlled converter with reduced line current harmonics is presented. It is shown that these harmonics are reduced below limits imposed by relevant international standards governing the generation and injection of harmonics into the distribution systems by equipment which draws current less than 16 A. The paper also demonstrates the use of a feedforward neural network (NN) for the prediction of the line current harmonics. The neural network predicted results compared favorably with the simulation results and hence were also within the limits of the harmonic regulations.

Harmonic Analysis

Harmonic

Feed forward

Line (geometry)

Feedforward neural network

10.1109/isiea.2010.5679493

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Linearization of the First-order TDTL Using a Pre-distortion Scheme

Omar A. Al-Kharji Prasad Ponnapalli Nader Anani Saleh R. Al‐Araji Mahmoud Al‐Qutayri

In this paper the architecture of a first-order time delay digital tanlock loop (TDTL) with linearized phase detector (PD) using a feedforward pre-distortion technique is proposed. The technique, which has been traditionally used with power amplifiers, involves pre-distorting the input signal to the TDTL so as to compensate for the nonlinearity of the TDTL caused by its fixed time delay unit. The performance of the proposed system was evaluated in noisy and noise-free environments and compared with the original TDTL system using sudden changes in input signal frequency using MATLAB/Simulink. In both cases, results indicate that the performance of the proposed TDTL with pre-distortion outperforms that of the original TDTL system. (5 pages)

Distortion (music)

Feed forward

Linearization

Phase distortion

SIGNAL (programming language)

10.1049/ic.2012.0099

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Synchronization of a Renewable Energy Inverter with the Grid

Smart innovation, systems and technologies (2012)

Nader Anani Omar Al-Kharji Al-Ali Prasad Ponnapalli Saleh R. Al‐Araji Mahmoud Al‐Qutayri

Synchronizing

10.1007/978-3-642-27509-8_18

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A new algorithm for completing fragmented boundaries in images

Dalil Benchebra Nader Anani Prasad Ponnapalli Abdel–Razzak Natsheh

In any image processing system, the process of detection and identification of individual objects within an image is often impeded by the presence of gaps in the boundaries of different objects. Various algorithms have been described in the literature for closing such gaps and hence completing fragmented boundaries making the detection of different objects within an image easier. In this paper a new algorithm, the Growing Circle Algorithm, is presented for completing broken boundaries. The algorithm was initially developed for completing the eyes' boundaries in medical images of the human face. In particular, the algorithm has been successfully implemented in a medical image processing system for diagnosis of paranasal sinuses conditions. In addition, the algorithm has also been successfully used for estimating and completing boundaries of varying geometry, complexity and degree of fragmentation.

Algorithm design

Identification

10.1109/csndsp16145.2010.5580326

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The representation of domain knowledge in intelligent training systems

R.R. Leitch Prasad Ponnapalli Alan Falconer Slater

The ESPRIT project 2615 ITSIE, aims to utilise ITS techniques to develop a generic framework for the development of training systems. A major aspect of this project is the use of the qualitative modelling techniques to meet the needs of current training systems. The project has recognised the importance of clearly establishing the types of skills and 'expertise' required of the trainee. The authors believe that this expertise exists in various forms and should be supported by appropriate representational tools. A systematic classification of domain knowledge for intelligent training is presented as used within the ITSIE project. Based on earlier studies on the classification of the behaviour of humans in industrial environments, it is proposed that the domain knowledge be classified into two main categories: domain expertise and domain simulation. The proposed classification and tools provide a coherent way of representing domain knowledge in ITS and allow the use of multiple models in a model switching framework for effective training.

Representation

Domain model

Source

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Dual Time Delay Digital Tanlock Loop with improved performance

Omar Al-Kharji Al-Ali Nader Anani Prasad Ponnapalli Saleh R. Al‐Araji Mahmoud Al‐Qutayri

A dual Time Delay Digital Tanlock Loop (D-TDTL) topology is proposed in this work. The system consists of a stacked dual loop of which the top one acts as a Frequency Lock loop (FLL) for the bottom loop, while the latter is a phase lock loop (PLL) that enhances the overall phase of the system. The main advantage of the proposed system is the large reduction of phase noise or jitter which makes it well suited to operate in noisy environment. The performance of the D-TDTL system was demonstrated using frequency shift keying (FSK) input signal with AWGN noise.

Delay-locked loop

Dual loop

Frequency-shift keying

Lock (firearm)

10.1109/eurocon.2011.5929178

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Citations (3)