Tariq S. Durrani

A RKHS interpolator-based graph matching algorithm

We present an algorithm for performing attributed graph matching. This algorithm is derived from a generalized framework for describing functionally expanded interpolators which is based on the theory of reproducing kernel Hilbert spaces (RKHS). The algorithm incorporates a general approach to a wide class of graph matching problems based on attributed graphs, allowing the structure of the graphs to be based on multiple sets of attributes. No assumption is made about the adjacency structure of the graphs to be matched.

A new adaptive functional-link neural-network-based DFE for overcoming co-channel interference

A new approach for the decision feedback equalizer (DFE) based on the functional-link neural network is described. The structure is applied to the problem of adaptive equalization in the presence of intersymbol interference (ISI), additive white Gaussian noise, and co-channel interference (CCI). It is shown through simulation results for a severe amplitude distorted co-channel system that the decision feedback functional-link equalizer (DFFLE) provides significantly superior bit-error rate (BER) performance characteristics compared to the conventional DFE, the linear transversal equalizer (LTE), the nonlinear radial basis function (RBF) neural-network-based structures and the feed-forward functional-link equalizer (FFLE)-based structures. The DFFLE is also shown to have a significantly simpler computational requirement relative to the RBF and the FFLE.

Sentic Computing for patient centered applications

Next-generation patients are far from being peripheral to health-care. They are central to understanding the effectiveness and efficiency of services and how they can be improved. Today a lot of patients are used to reviewing local health services on-line but this social information is just stored in natural language text and it is not machine-accessible and machine-processable. To distil knowledge from this extremely unstructured information we use Sentie Computing, a new opinion mining and sentiment analysis paradigm which exploits AI and Semantic Web techniques to better recognize, interpret and process opinions and sentiments in natural language text. In particular, we use a language visualization and analysis system, a novel emotion categorization model, a resource for opinion mining based on a web ontology and novel techniques for finding and defining topic dependent concepts, namely spectral association and CF-IOF weighting respectively.

Frequency estimation in the presence of Doppler spread: performance analysis

We are concerned with the estimation of the frequency of a complex sinusoid that has been corrupted by complex-valued multiplicative and additive noise. This problem is important in many applications including array processing in the case of spatially distributed sources and synchronization in the context of time-selective channels. The multiplicative noise smears the spectral line due to the sinusoid. This smearing, which is often called Doppler spreading, may significantly degrade the estimation accuracy. The goal of this paper is to analytically assess this degradation. The finite-sample Cramer-Rao bounds (CRBs) are derived, and closed-form expressions are given for the large-sample CRB. The latter gives insights into the effective coherent and noncoherent SNRs for frequency estimation. We then analyze the accuracy of frequency estimators that are based on the angles of the sample covariances. Simulations results are presented to illustrate the theoretical results.

MANAGING THE TECHNOLOGY ACQUISITION PROCESS

Abstract Technology acquisition plays a key role in the management of technology in industrial organisations. To provide a competitive advantage to organisation whose primary business focus is on product development, change management and market success, a conceptual model was developed which provides a formalised approach to technology acquisition, involving a staged process for identifying a technology; a methodology for acquiring the technology, and a decision-making process for sourcing the technology. To ensure widespread application and ease of operation, the model is realised in a groupware environment — MANTRA — a structured resource that represents a decision-making process integrating product attributes and marketplace requirements with the technology acquisition process.

Temporal and spatial sampling influence on the estimates of superimposed narrowband signals: when less can mean more

This paper addresses the influence that the sampling locations have on the estimated frequencies of superimposed sinusoids. This problem has application in harmonic time-series analysis or direction-finding phased-array systems. Generalized mathematical bounds are developed in terms that are independent of the array locations and have an intuitively appealing physical interpretation. They establish the influence of the sampling locations on the variance of the frequency estimate and the limit at which two sources can be resolved using signal subspace estimators. For the resolution criteria, an expression dominated by the fourth central moment of the sensor locations expresses the resolving ability of the sensing array, irrespective of the array aperture or number of sensors. Increasing the fourth central moment increases an arrays resolution ability. The commonly accepted notion that resolution necessarily depends on the array aperture is misleading and, indeed, that fewer snapshots from a reduced aperture array can outperform a larger array of more elements. For the estimator variance criteria, it is found that the product of the number of sensors and the second central moment (array variance) characterizes the estimator variance lower bound. The metrics developed demonstrate that the sampling topology is itself an important factor in determining the performance of the sampling system (and not the covariance lags sampled or the aperture spanned). Simulations are used to describe the results.

IP protection of DSP algorithms for system on chip implementation

Silicon technology has now advanced to the point that there is a serious mismatch in the time taken to design advanced silicon-based systems and the time to market for any new product or product derivative. To obviate this delay, a new paradigm is emerging based on intellectual property (IP) exchange, where designers and differing companies share subsystems (virtual cores) between themselves to reduce design time to acceptable levels. To this end, over 150 companies including all the major players formed the Virtual Socket Interface Alliance in March 1997. The protection of IP has become a serious issue as intercompany subsystem design exchange becomes more commonplace. This paper presents new techniques to protect the IP of virtual cores that implement digital signal processing (DSP) algorithms. The approach involves embedding codewords into the design of fundamental signal processing algorithms such as digital filters and the DFT in such a way that proof of authorship can be retained, and, if required, easily identified. The techniques discussed can be adapted to protect other fundamental DSP algorithms such as convolution and correlation. The protection of IP via watermarking techniques is increasingly being applied at all levels of design. It is particularly advantageous if such techniques are applied at the highest abstraction levels in the design flow, and if such techniques are applied at basic algorithm level, they become very difficult to detect at lower levels of system design.

Managing the product development process - (Part I: an assessment)

Recent studies have indicated that a companys chances of success in launching new products is dependent upon the management of the new product development process. The increasing rate of technological change coupled with increasing global competition, means that a high rate of new product development and introduction in the marketplace is vital to a companys continued growth and long-term survival. In this part, methodologies for new product development, including (a) Phased Development, (b) Stage/Gate Models, (c) Product and Cycle -time Excellence - PACE and, (d) Total Design, are investigated. The strengths and weaknesses of each methodology are assessed and proposals for improved management of the new product development process in manufacturing are discussed.

Asymptotic performance of eigenstructure spectral analysis methods

This paper considers some asymptotic statistical properties of covarianee eigenstructure spectral analysis techniques. It is shown that when the signal model is of the appropriate form, and the observations are Gaussian, the signal parameter estimates, obtained by locating the nulls in the eigen-spectrum, are asymptotically zero mean normal random variables. Based on this observation, the paper then considers the formation of confidence regions for the signal parameters. The paper presents the general case of a multi-dimensional eigenstructure algorithm, which estimates one or more parameters of each signal in the observed data.

Direction of arrival estimation using artificial neural networks

The maximum likelihood estimator is the optimal estimator of the direction of sources, but it requires the minimization of a complex, multimodal, multidimensional cost function. A neural optimization procedure is presented that does not require an initial estimate of the direction of the sources and offers the potential of real-time solutions to the direction of arrival problem by utilizing the fast relaxation properties of the Hopfield network. A modification based on an iterated descent procedure is introduced into the Hopfield model dynamic equation to increase the probability of convergence to the global optimum. The algorithms are implemented on an array of closely coupled transputers that perform the random asynchronous neural updates in parallel. The mapping is achieved using a technique called chaotic relaxation. Simulation results are presented to characterize the performance of the neural approach in terms of the variance of the estimates of source directions and the time required for the computation of the estimates. >