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The Finite-Difference Time-Domain Method (FDTD) is a very powerful numerical method for the full wave analysis electromagnetic phenomena. Due to its flexibility, it can be used to solve numerous electromagnetic scattering problems on microwave circuits, dielectrics, and electromagnetic absorption in biological tissue at microwave frequencies. However, it needs so much computation time to simulate microwave integral circuits by applying the FDTD method. If the structure we simulated is complicated and we want to obtain accurate frequency domain scattering parameters, the simulation time will be so much longer that the efficiency of simulation will be bad as well. Therefore, in the thesis, we introduce an artificial neural networks (ANN) method called ¡§Finite Impulse Response Neural Networks (FIRNN)¡¨ can speed up the FDTD simulation time. In order to boost the efficiency of the FDTD simulation time by stopping the simulation after a sufficient number of time steps and using FIRNN as a predictor to predict time series signal.

Response reconstruction is used to obtain accurate replication of vehicle structural responses of field recorded measurements in a laboratory environment, a crucial step in the process of Accelerated Destructive Testing (ADT). Response Reconstruction is cast as an inverse problem whereby the desired input is inferred using the measured outputs of a system. ADT typically involves large shock loadings resulting in a nonlinear response of the structure. A promising linear regression technique known as Spanning Basis Transformation Regression (SBTR) in con- junction with non-overlapping windows casts the low dimensional nonlinear problem as a high dimensional linear problem. However, it is determined that the original implementation of SBTR struggles to invert a broader class of sensor configurations. A new windowing method called AntiDiagonal Averaging (ADA) is developed to overcome the shortcomings of the SBTR im- plementation. ADA introduces overlaps within the predicted time signal windows and averages them. The newly proposed method is tested on a numerical quarter car model and is shown to successfully invert a broader range of sensor configurations as well as being capable of describing nonlinearities in the system. / Dissertation (MEng)--University of Pretoria, 2021. / Mechanical and Aeronautical Engineering / MEng / Unrestricted

Yes / The Daubechies, coiflet and symlet wavelets, with properties of orthogonal wavelets are suitable for multicarrier transmission over band-limited channels. It has been shown that similar wavelets can be constructed by Lagrange approximation interpolation. In this work and using established wavelet design algorithms, it is shown that ideal filters can be approximated to construct new orthogonal wavelets. These new wavelets, in terms of BER behave slightly better than the wavelets mentioned above, and much better than biorthogonal wavelets, in multipath channels with additive white Gaussian noise (AWGN). It is shown that the construction, which uses a simple simultaneous solution to obtain the wavelet filters from the ideal filters based on established wavelet design algorithms, is simple and can easily be reproduced.

The interconnection of molecular machines with different functionalities to form molecular communication systems can increase the number of design possibilities and overcome the limited reliability of the individual molecular machines. Artificial information exchange using molecular signals would also expand the capabilities of single engineered cell populations by providing them a way to cooperate across heterogeneous cell populations for the applications of synthetic biology and lab-on-a-chip systems. The realization of molecular communication systems necessitates analysis and design of the communication channel, where the information carrying molecular signal is transported from the transmitter to the receiver. In this thesis, significant progress towards the use of microfluidic channels to interconnect molecular transmitter and receiver pairs is presented. System-theoretic analysis of the microfluidic channels are performed, and a finite-impulse response filter is designed using microfluidic channels. The spectral density of the propagation noise is studied and the additive white Gaussian noise channel model is developed. Memory due to inter-diffusion of the transmitted molecular signals is also modeled. Furthermore, the interference modeling is performed for multiple transmitters and its impact on the communication capacity is shown. Finally, the efficient sampling of the signal transduction by engineered bacterial receivers connected to a microfluidic channel is investigated for the detection of the pulse-amplitude modulated molecular signals. This work lays the foundation for molecular communication over microfluidic channels that will enable interconnection of engineered molecular machines.

The thesis presents algorithms based on a linear algebraic solution for the identification of the parameters of the FIR system using only higher order statistics when only the output of the system corrupted by additive Gaussian noise is observed. All the traditional parametric methods of estimating the parameters of the system have been based on the 2nd order statistics of the output of the system. These methods suffer from the deficiency that they do not preserve the phase response of the system and hence cannot identify non-minimum phase systems. To circumvent this problem, higher order statistics which preserve the phase characteristics of a process and hence are able to identify a non-minimum phase system and also are insensitive to additive Gaussian noise have been used in recent years. Existing algorithms for the identification of the FIR parameters based on the higher order cumulants use the autocorrelation sequence as well and give erroneous results in the presence of additive colored Gaussian noise. This problem can be overcome by obtaining algorithms which do not utilize the 2nd order statistics. An existing relationship between the 2nd order and any Ith order cumulants is generalized to a relationship between any two arbitrary k, Ith order cumulants. This new relationship is used to obtain new algorithms for FIR system identification which use only cumulants of order > 2 and with no other restriction than the Gaussian nature of the additive noise sequence. Simulation studies are presented to demonstrate the failure of the existing algorithms when the imposed constraints on the 2nd order statistics of the additive noise are violated while the proposed algorithms perform very well and give consistent results. Recently, a new algebraic approach for parameter estimation method denoted the Linear Combination of Slices (LCS) method was proposed and was based on expressing the FIR parameters as a linear combination of the cumulant slices. The rank deficient cumulant matrix S formed in the LCS method can be expressed as a product of matrices which have a certain structure. The orthogonality property of the subspace orthogonal to S and the range space of S has been exploited to obtain a new class of algorithms for the estimation of the parameters of a FIR system. Numerical simulation studies have been carried out to demonstrate the good behaviour of the proposed algorithms. Analytical expressions for the covariance of the estimates of the FIR parameters of the different algorithms presented in the thesis have been obtained and numerical comparison has been done for specific cases. Numerical examples to demonstrate the application of the proposed algorithms for channel equalization in data communication and as an initial solution to the cumulant matching nonlinear optimization methods have been presented.

Το αριθμητικό σύστημα υπολοίπων (RNS) έχει προταθεί ως ένας τρόπος για επιτάχυνση των αριθμητικών πράξεων του πολλαπλασιασμού και της πρόσθεσης. Ένα από τα σημαντικά πλεονεκτήματα της χρήσης του RNS είναι ότι οδηγεί σε κυκλώματα που έχουν το χαρακτηριστικό της χαμηλής κατανάλωσης. Πιο συγκεκριμένα στην παρούσα διατριβή γίνεται μια αναλυτική μελέτη πάνω στην ταχύτητα διεξαγωγής της πράξης του πολλαπλασιασμού και της άθροισης. Ο λόγος που γίνεται αυτό είναι διότι οι εφαρμογές επεξεργασίας σήματος χρησιμοποιούν ιδιαιτέρως τις προαναφερθείσες πράξεις. Επίσης γίνεται μελέτη της ισχύος που καταναλώνεται κατά την επεξεργασία ενός σήματος με τη χρήση των προτεινόμενων αριθμητικών κυκλωμάτων. Ιδιαίτερη έμφαση δίνεται στη χρήση απλών αρχιτεκτονικών τις οποίες μπορούν τα εργαλεία σύνθεσης να διαχειριστούν καλύτερα παράγοντας βέλτιστα κυκλώματα. Τέλος η διατριβή μελετά τα προβλήματα διακύμανσης των παραμέτρων του υλικού που αντιμετωπίζει η σύγχρονη τεχνολογία κατασκευής ολοκληρωμένων κυκλωμάτων. Συγκεκριμένα σε τεχνολογία μικρότερη των 90nm παρατηρείται το φαινόμενο ίδια στοιχεία κυκλώματος να συμπεριφέρονται με διαφορετικό τρόπο. Το φαινόμενο αυτό γίνεται σημαντικά πιο έντονο σε τεχνολογίες κάτω των 45nm. Η παρούσα διατριβή προτείνει λύσεις βασισμένες στην παραλληλία και την ανεξαρτησία των επεξεργαστικών πυρήνων που παρέχει το RNS, για να αντιμετωπίσει το συγκεκριμένο φαινόμενο. / The Residue Number System (RNS) has been proposed as a means to speed up the implementation of multiplication-addition intensive applications, commonly found in DSP. The main benefit of RNS is the inherent parallelism, which has been exploited to build efficient multiply-add structures, and more recently, to design low-power systems. In particular, this dissertation deals with the delay complexity of the multiply-add operation (MAC). The reason for this is that DSP applications are MAC intensive and hence this dissertation proposes solutions to increase the speed of processing. Furthermore, the study of the multiply-add operations is extended to power consumption matters. The dissertation focus on simple architectures such that EDA tools produce efficient in both power and delay, synthesized circuits. Finally the dissertation deals with variability matters that came up as the vlsi technology shrinks below 90nm. Variability becomes unaffordable especially for the 45nm technology node. This dissertation proposes solutions based on parallelism and the independence of the RNS cores to derive variation-tolerant architectures.

Submitted by JULIO CEZAR UZINSKI null (uzinski.jc@gmail.com) on 2016-12-15T21:43:22Z No. of bitstreams: 1 Uzinski JC.pdf: 2380247 bytes, checksum: 910b14a40501433136262e638e586b5f (MD5) / Approved for entry into archive by Felipe Augusto Arakaki (arakaki@reitoria.unesp.br) on 2016-12-20T16:20:21Z (GMT) No. of bitstreams: 1 uzinski_jc_dr_ilha.pdf: 2380247 bytes, checksum: 910b14a40501433136262e638e586b5f (MD5) / Made available in DSpace on 2016-12-20T16:20:21Z (GMT). No. of bitstreams: 1 uzinski_jc_dr_ilha.pdf: 2380247 bytes, checksum: 910b14a40501433136262e638e586b5f (MD5) Previous issue date: 2016-11-25 / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. Para ilustrar o funcionamento e as vantagens da técnica proposta, alguns exemplos de decomposição de sinais no contexto de processamento de sinais mostrando que ela proporciona os mesmos coeficientes wavelet que a transformada wavelet rápida, e uma aplicação em controle através de realimentação dinâmica de estados também são apresentados nesta tese. / This thesis presents a state-space parameterization for the fast wavelet transform. This parameterization is based on orthonormal basis functions and finite impulse response filters at the same time, since the fast wavelet transform is an algorithm, which converts a signal in the time domain into a sequence of coefficients based on an orthogonal basis of small finite wavelet functions. Advantages presented by both proposals are incorporated. Finite impulse response systems have attractive properties, for instance, computational and analytical advantages, BIBO stability and robustness guarantee to some parameter changes, and others. On the other hand, orthonormal basis functions have some characteristics that make them attractive for dynamic systems modeling, examples are, output recursion absence, not requiring prior regression vector exact structure knowledge; possibility of increasing the model representation capacity by increasing the number of orthonormal functions employed; natural outputs uncoupling in multivariable models; tolerance to unmodeled dynamics, and others. Furthermore, the state-space realization is minimal. The contribution of this work consists in the development of a state-space realization for a wavelet filter bank, with the explicit presence of the parameters that can be freely adjusted, keeping perfect-reconstruction and orthonormality guarantees. In order to illustrate advantages and how the proposed technique works, some decomposition examples in signal processing context are presented showing that it provides the same wavelet coefficients as the fast wavelet transform, and an application on dynamic state feedback control is also presented in this thesis. / CNPq: 160545/2013-7