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A unified data model is presented which offers a superset of the data modelling constructs and semantic integrity constraints of major existing data models. These semantic integrity constraints are both temporal and non-temporal, and are classified by constraint type (attribute, membership, set, temporal) and semantic integrity category (type, attribute value, intra-tuple, intra-class, inter-class). The unified data model has an onion-skin architecture comprising a DB state, DB state transition and temporal models, the realization of all three providing the facilities of a temporal DB. The DB state model is concerned with object-entities and the DB state transition model deals with event-entities and the non-destructive updating of data. A third species of entity is the rule. The temporal model conveys the times of object existence, event occurrence, retro-/post-active update, data error correction, the historical states of objects, and Conceptual Schema versions. Times are either instantaneous/durational time-points or time-intervals. Object and event classes are organized along the taxonomic axes of aggregation, association, categorization and generalization. Semantic integrity constraints and attribute inheritance are defined for each kind of data abstraction. A predicate logic oriented Conceptual Schema language is outlined for specifying class definitions, abstraction and transformation rules, and semantic integrity constraints. Higher-order abstraction classes are primarily defined in terms of the constraints for their lower-order, definitive classes. Transformation rules specify update dependencies between classes. Support is shown for the major features of the main semantic data models, and a token implementation is presented.

This thesis is concerned with the Numerical Solution of Partial Differential Equations. Initially some definitions and mathematical background are given, accompanied by the basic theories of solving linear systems and other related topics. Also, an introduction to splines, particularly cubic splines and their identities are presented. The methods used to solve parabolic partial differential equations are surveyed and classified into explicit or implicit (direct and iterative) methods. We concentrate on the Alternating Direction Implicit (ADI), the Group Explicit (GE) and the Crank-Nicolson (C-N) methods. A new method, the Splines Group Explicit Iterative Method is derived, and a theoretical analysis is given. An optimum single parameter is found for a special case. Two criteria for the acceleration parameters are considered; they are the Peaceman-Rachford and the Wachspress criteria. The method is tested for different numbers of both parameters. The method is also tested using single parameters, i. e. when used as a direct method. The numerical results and the computational complexity analysis are compared with other methods, and are shown to be competitive. The method is shown to have good stability property and achieves high accuracy in the numerical results. Another direct explicit method is developed from cubic splines; the splines Group Explicit Method which includes a parameter that can be chosen to give optimum results. Some analysis and the computational complexity of the method is given, with some numerical results shown to confirm the efficiency and compatibility of the method. Extensions to two dimensional parabolic problems are given in a further chapter. In this thesis the Dirichlet, the Neumann and the periodic boundary conditions for linear parabolic partial differential equations are considered. The thesis concludes with some conclusions and suggestions for further work.

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This thesis explores various coding aspects of multiple access communications, mainly for spread spectrum multiaccess(SSMA) communications and collaborative coding multiaccess(CCMA) communications. Both the SSMA and CCMA techniques permit efficient simultaneous transmission by several users sharing a common channel, without subdivision in time or frequency. The general principle behind these two multiaccess schemes is that one can find sets of signals (codes) which can be combined together to form a composite signal; on reception, the individual signals in the set can each be recovered from the composite signal. For the CCMA scheme, the isolation between users is based on the code structure; for the SSMA scheme, on the other hand, the isolation between users is based on the autocorrelation functions(ACFs) and crosscorrelation functions (CCFs) of the code sequences. It is clear that, in either case, the code design is the key to the system design. For the CCMA system with a multiaccess binary adder channel, a class of superimposed codes is analyzed. It is proved that every constant weight code of weight w and maximal correlation λ corresponds to a subclass of disjunctive codes of order T < w/λ. Results related to the decomposition of the disjunctive codes in the noiseless and noisy cases are derived. Decoding algorithms for both the noiseless and the noisy cases are proposed. For the CCMA system operating over a multiaccess Q-ary adder channel, a class of cyclic uniquely decodable codes is proposed and analyzed by employing cyclic codes with symbols from an arbitrary finite integer rings. A very low complexity decoding procedure is presented. For a synchronous SSMA system, a new approach employing orthogonal complementary sets is presented; the properties of such orthogonal complementary sets are studied in detail. Recursive formulas for constructing orthogonal complementary sets are given. Methods for synthesizing new orthogonal complementary sets from known ones with the same dimensions are also discussed. For an asynchronous SSMA system, several new spreading codes are presented and studied: 1. A new class of polyphase codes with two-valued periodic ACF and CCF properties is derived. It is proved that, for a given prime length L > 3, the out-of-phase ACFs and CCFs of the codes are constant and equal to √L. In addition, all codes of the same length are mutually orthogonal. 2. Maximal length sequences (m-sequences) over Gaussian integers, suitable for use with QAM modulation, are considered. Two sub-classes of m-sequences with quasi-perfect periodic autocorrelations are obtained. The CCFs between the decimated m-sequences are studied. By applying a simple operation, it is shown that some m-sequences over rational and Gaussian integers can be transformed into perfect sequences with impulsive ACFs. 3. Frank codes and Chu codes have perfect periodic ACFs and optimum periodic CCFs. In addition, it is shown that they also have very favourable nonperiodic ACFs; some new results concerning the behaviour of the nonperiodic ACFs are derived. Further, it is proved that the sets of combined Frank/Chu codes, which contain a larger number of codes than either of the two constituent sets, also have very good periodic CCFs. Based on Frank codes and Chu codes, two interesting classes of real-valued codes with good correlation properties are defined. It is shown that these codes have periodic complementary properties and good periodic and nonperiodic ACF/CCFs. Finally, a hybrid CCMA/SSMA coding scheme is proposed. This new hybrid coding scheme provides a very flexible and powerful multiple accessing capability and allows simple and efficient decoding. Given an SSMA system with K users and a CCMA system with N users, where at most T users are active at any time, then the hybrid system will have K . N users with at most T.K users active at any time. The hybrid CCMA/SSMA coding scheme is superior to the individual CCMA system or SSMA system in terms of information rate, number of users, decoding complexity and external interference rejection capability.

This thesis considers the classification of physical states in a simplified gearbox using acoustical data and simple time domain signal shape characterisation techniques allied to a basic feedforward multi-layer perceptron neural network. A novel extension to the signal coding scheme (TES), involving the application of energy based shape descriptors, was developed. This sought specifically to improve the techniques suitability to the identification of mechanical states and was evaluated against the more traditional minima based TES descriptors. The application of learning based identification techniques offers potential advantages over more traditional programmed techniques both in terms of greater noise immunity and in the reduced requirement for highly skilled operators. The practical advantages accrued by using these networks are studied together with some of the problems associated in their use within safety critical monitoring systems.Practical trials were used as a means of developing the TES conversion mechanism and were used to evaluate the requirements of the neural networks being used to classify the data. These assessed the effects upon performance of the acquisition and digital signal processing phases as well as the subsequent training requirements of networks used for accurate condition classification. Both random data selection and more operator intensive performance based selection processes were evaluated for training. Some rudimentary studies were performed on the internal architectural configuration of the neural networks in order to quantify its influence on the classification process, specifically its effect upon fault resolution enhancement.The techniques have proved to be successful in separating several unique physical states without the necessity for complex state definitions to be identified in advance. Both the computational demands and the practical constraints arising from the use of these techniques fall within the bounds of a realisable system.

The thesis is concerned with serial data transmission at 9600 bit/sec over a voiceband channel, where the main impairments are additive noise and intersymbol interference, and the latter varles slowly with time. The thesis includes a brief description of the ionospheric propagation medium and presents an equivalent baseband model of the HF channel, suitable for computer simulation of quadrature amplitude modulation (QAM) systems. A study of 16-point QAM signals transmitted over voiceband HF channels is then carr-iod out usj-ng the given channel model. Several cost effective near-maximum-likelihood detection processes have been developed for HF modems. Each detector is here preceded by an adaptive linear filter that is adjusted to make the sampled impulse response of the channel and filter minimum phase. These detectors require an accurate knowledge of the sampled impulse response of the channel, if their full potential is to be achieved. The results of computer-simulation tests on the near-maximum-likelihood detectors are given, where these tests assume that other receiver operations such as channel estimation and adaptive linear filtering, together with element timing synchronisation and Doppler shift correction, are carried out perfectly. A recently developed HF channel estimator employing a simple feedforward transversal-filter and requiring knowledge of the number of skywaves is next investigated and a starting up procedure is developed for such an estimator. The technique is then made fully adaptive in the sense that it continues to operate correctly when the number of skywaves changes. Results of computer simulation tests are then presented showing the performance of the above detectors when operating with a channel estimator and adaptive linear filtering. Finally modem synchronisation is studied and various techniques of element timing and carrier frequency synchronisation are proposed.

This thesis investigates various detection processes that operate with known time invariant channels. The investigations are divided into two main areas, the first of which involves uncoded digital signals. Three different detection processes have been studied here and some promising systems have been developed from these. The first of the detection processes is an iterative detection process whereas the second detection process involves the linear filtering of the received signal. Binary signals are considered in the investigations here. The third detection process achieves the near-maximum likelihood detection of a 16-point QAM digital signal transmitted over a telephone circuit at 9600 bits/second. The detector here operates on the received sample values directly without using any complex prefiltering. The second area of investigation covered in this thesis involves coded digital signals. Binary and 16-point QCM signals have been considered here. Rate2 and 3 non-systematic convolutional codes with optimum free distance have been used in conjunction with the appropriate Gray codes for the encoding of the signals. At the receiving end, a joint near-maximum likelihood detection/decoding process is used. Computer simulation tests have shown that the system improves the tolerance to Gaussian noise over the corresponding uncoded system at low error rates.