Discrete cosine transform-only and discrete sine transform-only windowed update algorithms for shifting data with hardware implementation

Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST) are widely used in image and data compression applications. To process the DCT or DST of a signal a portion of length N is extracted by windowing. By shifting the window point by point the entire signal can be processed. The algorithms are developed that are capable of updating the DCT and DST independently to reflect the modified window contents i.e. for calculating the DCT of the shifted sequence no DST coefficients are used and similarly for calculating the DST of the shifted sequence no DCT coefficients are used. These algorithms constitute an improvement over previous DCT/DST update algorithms as it establishes independence between the DCT and the DST. The update algorithms used to calculate the transform of the shifted sequence uses less computation as compared to directly evaluating the modified transform via standard fast transform algorithms. Firstly, the r-point, 1 = r = N-1, update algorithms are derived in the presence of the rectangular window. Thereafter, one point independent windowed update in the presence of split-triangular, Hanning, Hamming and Blackman windows are developed. The algorithms were implemented in C language to test their correctness. Thereafter the hardware circuits capable of computing the independent update of DCT-II for the rectangular window of size N=8 and step size of 1 and 4 are developed. The windowed update algorithms are derived for DCT and DST type-I through IV, however the hardware implementation of type-II is given as it is the most frequently used transform

Advanced Modulation/Demodulation Schemes For Wireless Communications

Le modulazioni a fase continua CPM ("Continuous phase modulations") e le modulazioni multiportante, sono due schemi di modulazione che sembrano essere molto adatti a trasmissioni wireless. In particolare, le CPM formano un'ampia classe di modulazioni caratterizzata da fase continua ed inviluppo costante e quindi particolarmente efficienti sia energeticamente che spettralmente. Inoltre, la natura ricorsiva del modulatore le rende particolarmente adatte in schemi di concatenazione seriale, decodificati iterativamente. I due problemi maggiori nel progetto di sistemi pratici che impieghino segnale CPM sono l'elevata complessità nel ricevitore (in termini di filtri di "front end" e di numero di stati nel trellis) e l'elevata sensibilità alla non perfetta sincronizzazione di fase. Nella seguente tesi, si analizzano i segnali CPM prima di tutto dal punto di vista capacitivo. Applicando il metodo di Arnold e Loeliger, si valuta l'informazione media mutua delle CPM su canale additivo gaussiano bianco (AWGN) e su canali affetti da rumore di fase. In particolare, si considera un processo di rumore di fase di Wiener ed anche un processo di rumore di fase di maggior interesse pratico, ovvero il SATMODE, tipico di canali satellitari. Inoltre, siccome nonostante le buone proprietà spettrali delle CPM, le modulazioni lineari spesso offrono una maggiore efficienza spettrale (specialmente per valori di efficienza spettrale medio-alti), si propone un metodo di massimizzazione dell'efficienza spettrale, ottenuto ottimizzando le probabilità di ingresso degli ingressi. Si restringe la ricerca ad ingressi di Markov di un certo ordine e si ottiene di conseguenza la capacità di Markov. Secondariamente, allo scopo di superare uno dei principali svantaggi delle CPM, si affronta il problema della derivazione di algoritmi a complessità ridotta per segnali CPM. In particolare, si considerano CPM concatenate serialmente con un codice a correzione di errori (schemi SCCPM). Questi ricevitori sono particolarmente interessanti poiché possono assumere praticamente le stesse prestazioni del ricevitore ottimo ma con una complessità nettamente ridotta. La complessità del ricevitore complessivo dipende principalmente dal rivelatore CPM, e quindi ci si concentra sulla derivazione di schemi di rivelazione a bassa complessità a partire da una strategia di rivelazione a massima probabilità a posteriori (MAP) sui simboli, dato che tale tecnica permette di avere stime di affidabilità sulle decisioni del rivelatore, necessarie per schemi SCCPM. Si prendono in considerazione due approcci per la derivazione di algoritmi: il primo basato su rappresentazioni alternative del segnale CPM, e l'altro basato su tecniche di riduzione di complessità del trellis. Si considera anche combinazioni dei due approcci. In particolare, per ogni formato CPM considerato si riesce sempre a trovare almeno un rivelatore a complessità ridotta, con praticamente le stesse prestazioni di quello ottimo. Si affronta quindi l'altro grande limite delle CPM (ovvero la sensibilità al rumore di fase) considerando algoritmi di rivelazione ad ingressi ed uscite "soft" (ovvero con stime di affidabilità sulle decisioni) per segnali CPM, in presenza di rumore di fase: la stima di fase è implementata congiuntamente alla rivelazione. Anche in questo caso si seguono due approcci: uno non-bayesiano, per il quale il rumore di fase è assunto come una quantità deterministica non nota al ricevitore, e l'altro bayesiano, che consiste nell'assumere un modello stocastico con cui modellizzare il rumore di fase nella derivazione dell'algoritmo di rivelazione. In particolare vengono proposti due modelli di rumore di fase, quello di Wiener e un altro modello statistico, qui derivato per descrivere il rumore di fase SATMODE. Si confrontano tutti gli algoritmi così ottenuti in termini di bit error rate (BER) e si confrontano questi risultati con quelli di informazione mutua precedentemente ottenuti. L'altro scenario considerato è rappresentato da schemi multiportante, utilizzati per trasmissioni digitali su canali doppiamente selettivi. Si comincia considerando la tecnica "orthogonal frequency-division multiplexing" (OFDM), che è un efficiente schema modulativo che fa parte della più ampia classe di modulazioni multiportante. OFDM è molto efficiente su canali selettivi in frequenza, siccome riesce a decomporli in un set di sottocanali, ortogonali e quindi privi di interferenza. Tuttavia il principale svantaggio dell'OFDM è l'elevata sensibilità alle variazioni temporali della risposta all'impulso del canale: in presenza di canali tempo-varianti si perde infatti l'ortogonalità fra le sottoportanti e si verifica interferenza. Ci sono quindi due possibili soluzioni: la prima prevede il progetto di ricevitori complessi con memoria o di complesse tecniche di equalizzazione. L'altra prevede il tentativo di prevenire il più possibile l'insorgere di interferenza, piuttosto che cercare di affrontarla al rivelatore. Nel presente lavoro di tesi, ci si rivolge al secondo approccio, derivando algoritmi di modulazione multiportante alternativi all'OFDM, allo scopo di ridurre la sensibilità alla tempo varianza del canale quando si considerano canali doppiamente selettivi. In dettaglio, si è dimostrato come, partendo da un generale sistema basato su banchi di filtri di trasmissione, si possa derivare un modello di sistema a tempo discreto sovracampionato, con lo scopo di fornire una via di implementazione pratica a diversi schemi di modulazione multiportante. Si è dimostrato come vari formati di modulazione multiportante già presenti in letteratura siano ricavabili come casi particolari di questo modello generale e come essi possano essere implementati in una modalità a complessità ridotta, ricorrendo ad opportune trasformate come la DFT (Discrete Fourier Transform), la DCT (Discrete Cosine Transform) e la DST (Discrete Sine Transform). Si sono quindi generalizzati questi schemi al caso di impulso prototipo non rettangolare, ma opportunamente progettato per ottenere la maggior compattezza possibile nel piano tempo-frequenza. Infine, ispirati dalla base di Wilson, che risulta essere un modo ingegnoso per progettare un set di segnali ortogonali e ben localizzati, si è derivato un nuovo sistema multiportante che sembra essere molto promettente per trasmissioni su canali doppiamente selettivi.Continuous phase modulations (CPMs) and multicarrier schemes, are two modulation schemes which seem to be very suitable for wireless communications. In particular, CPM is a wide class of modulations characterized by continuous phase and constant envelope, and hence, particularly efficient in power and bandwidth. Moreover, the recursive nature of the modulator, makes the CPM signaling formats attractive in serially concatenated schemes to be iteratively decoded. Two major problems in the design of practical systems employing CPM signals are the large complexity in the receiver (in terms of front end filters and number of states in the trellis) and the sensitiveness to inaccurate carrier synchronization. In the following thesis, first of all we analyze the CPM signal from an information theoretic point of view. We employ the method proposed by Arnold and Loeliger to compute the information rate of CPMs over Additive White Gaussian Noise (AWGN) channel and over channels affected by phase noise (PN). In particular, we consider a Wiener PN process and also a more practical phase noise process, typical of some satellite real channels (SATMODE PN). Moreover, since despite the good spectral properties of CPMs, linear modulation offer a much better efficiency, especially at medium and high spectral efficiencies, we propose a spectral efficiency maximization method, where we modify the input probability distribution. We restrict our search to Markov inputs of a given order and we denote the maximum found spectral efficiency, as Markov capacity. Secondly, in order to overcome one of the main CPM disadvantages, we face the problem of the design of reduced-complexity schemes for CPM signals. In particular, we consider serially-concatenated CPM (SCCPM) schemes, which admit a low-complexity receiver based on the serial concatenation of a CPM modulator with an outer error correcting code. These receivers are particularly interesting since they can achieve practically the same performance of an optimal receiver, in a low complexity way. The overall receiver complexity mainly depends on that of the CPM detector and hence, we focus on the derivation of reduced-complexity CPM detectors. In particular, we resort to detection algorithms derived from the maximum a posteriori probability (MAP) symbol detection strategy, since it allows us to obtain soft-decision algorithms, necessary in a SCCPM scheme. We consider two alternative approaches for algorithm derivation: one based on some alternative representations of the CPM signal, and the other based on techniques for trellis complexity reduction. The combination of the two approaches is also investigated. We will show that, for all the considered CPM formats, at least one low-complexity receiver with optimal performance, exists. Then, we address the other CPM main drawback (i.e., the sensitiveness to inaccurate carrier synchronization) by deriving reduced-complexity soft-input soft-output (SISO) detection algorithms suitable for iterative detection/decoding in the presence of PN. In particular, PN estimation is carried out jointly to the detection stage. In this case, we consider two approaches while deriving the algorithms: a non-Bayesian approach, which does not require any assumption on the statistical properties of the phase noise, since the PN is simply considered as a sequence of unknown parameters to be properly estimated, and the Bayesian approach, which consists of assuming a proper probabilistic model for the PN, and to exploit it for detection algorithm derivation. In particular, we propose Bayesian algorithms assuming both a Wiener PN model and a statistical model we have derived to describe SATMODE PN. We compare all the derived algorithms on channels affected by the two PN and we relate bit error rate (BER) results with information rate results previously obtained. The other considered scenario is represented by multicarrier schemes, employed in digital transmissions over doubly-selective channels. We start by considering orthogonal frequency-division multiplexing (OFDM), which is an efficient modulation scheme belonging to the wide class of multicarrier modulations, largely implemented in terrestrial networks. OFDM is particularly suitable for frequency selective, since OFDM decomposes linear time-invariant channels into a set of orthogonal, interference-free sub-channels. However, the main OFDM disadvantage is the strong sensitivity to the channel impulse response (CIR) time-variations: in the presence of a rapidly time-varying CIR, the orthogonality between the sub-carriers is destroyed and inter-carrier interference (ICI) appears. In such a case, we have two viable solutions; the first one is to derive receivers with memory, able to cope with the interference or complex equalization techniques. The second one is the design of modulation formats such as to reduce the interference (rather than to cope with it). We resort to the second approach, by deriving multicarrier modulation schemes alternative to the OFDM, to reduce the sensitivity to time-variations, in order to employ these modulations on doubly-selective channels In particular, starting from a general filter-bank system, we propose an oversampled discrete-time system model in order to get a practical implementation of various multicarrier modulation formats in realistic communication systems. We show that all multicarrier modulation formats can be derived from such a discrete-time model, with a general prototype filter (rather than with the classical rectangular filter) and a general time and frequency spacing between the coded symbols. In other words, we apply pulseshape techniques to all schemes, extending the techniques already proposed in the literature. Finally, inspired by the tight connection between multicarrier modulations and the Gabor communication theory, we consider the Wilson base, which is a clever way to design well-localized and orthogonal frames in the windowed Fourier framework, and we derive a novel practical multicarrier modulation scheme, very promising on doubly selective channels. It is important to remark that for all modulation schemes we will derive, a fast implementation exists

Image Restoration

This book represents a sample of recent contributions of researchers all around the world in the field of image restoration. The book consists of 15 chapters organized in three main sections (Theory, Applications, Interdisciplinarity). Topics cover some different aspects of the theory of image restoration, but this book is also an occasion to highlight some new topics of research related to the emergence of some original imaging devices. From this arise some real challenging problems related to image reconstruction/restoration that open the way to some new fundamental scientific questions closely related with the world we interact with

A parallel processing framework for spectral based computations

Includes abstract.Includes bibliographical references.Today, great advances have been made; however the tenet of ‘design first, figure out how to program later’ still lingers in the corridors of Silicon Valley. The focus of this study is however not on making a contribution to compilers or software development, nor on determining an efficient generic parallel processing architecture for all classes of computing. Instead, this study adopts a different design approach, where a class of computing is first selected and analyzed, before determining a suitable hardware structure which can be tailored to the class being considered. The class of computing under investigation in this work is Spectral Methods, which by its very nature, has its own processing and data communication requirements. The purpose of this study is to investigate the processing and data handling requirements of the Spectral Methods class, and to design a suitable framework to support this class. The approach is different from past traditions - the hardware framework is based on software requirements, and in a sense is designed for the processing required, rather that the other way around

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Intelligent Biosignal Processing in Wearable and Implantable Sensors

This reprint provides a collection of papers illustrating the state-of-the-art of smart processing of data coming from wearable, implantable or portable sensors. Each paper presents the design, databases used, methodological background, obtained results, and their interpretation for biomedical applications. Revealing examples are brain–machine interfaces for medical rehabilitation, the evaluation of sympathetic nerve activity, a novel automated diagnostic tool based on ECG data to diagnose COVID-19, machine learning-based hypertension risk assessment by means of photoplethysmography and electrocardiography signals, Parkinsonian gait assessment using machine learning tools, thorough analysis of compressive sensing of ECG signals, development of a nanotechnology application for decoding vagus-nerve activity, detection of liver dysfunction using a wearable electronic nose system, prosthetic hand control using surface electromyography, epileptic seizure detection using a CNN, and premature ventricular contraction detection using deep metric learning. Thus, this reprint presents significant clinical applications as well as valuable new research issues, providing current illustrations of this new field of research by addressing the promises, challenges, and hurdles associated with the synergy of biosignal processing and AI through 16 different pertinent studies. Covering a wide range of research and application areas, this book is an excellent resource for researchers, physicians, academics, and PhD or master students working on (bio)signal and image processing, AI, biomaterials, biomechanics, and biotechnology with applications in medicine

Novel load identification techniques and a steady state self-tuning prototype for switching mode power supplies

Control of Switched Mode Power Supplies (SMPS) has been traditionally achieved through analog means with dedicated integrated circuits (ICs). However, as power systems are becoming increasingly complex, the classical concept of control has gradually evolved into the more general problem of power management, demanding functionalities that are hardly achievable in analog controllers. The high flexibility offered by digital controllers and their capability to implement sophisticated control strategies, together with the programmability of controller parameters, make digital control very attractive as an option for improving the features of dcdc converters. On the other side, digital controllers find their major weak point in the achievable dynamic performances of the closed loop system. Indeed, analogto-digital conversion times, computational delays and sampling-related delays strongly limit the small signal closed loop bandwidth of a digitally controlled SMPS. Quantization effects set other severe constraints not known to analog solutions. For these reasons, intensive scientific research activity is addressing the problem of making digital compensator stronger competitors against their analog counterparts in terms of achievable performances. In a wide range of applications, dcdc converters with high efficiency over the whole range of their load values are required. Integrated digital controllers for Switching Mode Power Supplies are gaining growing interest, since it has been shown the feasibility of digital controller ICs specifically developed for high frequency switching converters. One very interesting potential benefit is the use of autotuning of controller parameters (on-line controllers), so that the dynamic response can be set at the software level, independently of output capacitor filters, component variations and ageing. These kind of algorithms are able to identify the output filter configuration (system identification) and then automatically compute the best compensator gains to adjust system margins and bandwidth. In order to be an interesting solution, however, the self-tuning should satisfy two important requirements: it should not heavily affect converter operation under nominal condition and it should be based on a simple and robust algorithm whose complexity does not require a significant increase of the silicon area of the IC controller. The first issue is avoided performing the system identification (SI) with the system open loop configuration, where perturbations can be induced in the system before the start up. Much more challenging is to satisfy this requirement during steady state operations, where perturbations on the output voltage are limited by the regular operations of the converter. The main advantage of steady state SI methods, is the detection of possible non-idealities occurring during the converter operations. In this way, the system dynamics can be consequently adjusted with the compensator parameters tuning. The resource saving issue, requires the development of äd-hocßelf-tuning techniques specifically tailored for integrated digitally controlled converters. Considering the flexibility of digital control, self-tuning algorithms can be studied and easily integrated at hardware level into closed loop SMPS reducing development time and R & D costs. The work of this dissertation finds its origin in this context. Smart power management is accomplished by tuning the controller parameters accordingly to the identified converter configuration. Themain difficult for self-tuning techniques is the identification of the converter output filter configuration. Two novel system identification techniques have been validated in this dissertation. The open loop SI method is based on the system step response, while dithering amplification effects are exploited for the steady state SI method. The open loop method can be used as autotunig approach during or before the system start up, a step evolving reference voltage has been used as system perturbation and to obtain the output filter information with the Power Spectral Density (PSD) computation of the system step response. The use of ¢§ modulator is largely increasing in digital control feedback. During the steady state, the finite resolution introduces quantization effects on the signal path causing low frequency contributes of the digital control word. Through oversampling-dithering capabilities of ¢§ modulators, resolution improvements are obtained. The presented steady state identification techniques demonstrates that, amplifying the dithering effects on the signal path, the output filter information can be obtained on the digital side by processing with the PSD computation the perturbed output voltage. The amount of noise added on the output voltage does not affect the converter operations, mathematical considerations have been addressed and then justified both with a Matlab/Simulink fixed-point and a FPGA-based closed loop system. The load output filter identification of both algorithms, refer to the frequency domain. When the respective perturbations occurs, the system response is observed on the digital side and processed with the PSD computation. The extracted parameters are the resonant frequency ans the possible ESR (Effective Series Resistance) contributes,which can be detected as maximumin the PSD output. The SI methods have been validated for different configurations of buck converters on a fixed-point closed loop model, however, they can be easily applied to further converter configurations. The steady state method has been successfully integrated into a FPGA-based prototype for digitally controlled buck converters, that integrates a PSD computer needed for the load parameters identification. At this purpose, a novel VHDL-coded full-scalable hybrid processor for Constant Geometry FFT (CG-FFT) computation has been designed and integrated into the PSD computation system. The processor is based on a variation of the conventional algorithm used for FFT, which is the Constant-Geometry FFT (CG-FFT).Hybrid CORDIC-LUT scalable architectures, has been introduced as alternative approach for the twiddle factors (phase factors) computation needed during the FFT algorithms execution. The shared core architecture uses a single phase rotator to satisfy all TF requests. It can achieve improved logic saving by trading off with computational speed. The pipelined architecture is composed of a number of stages equal to the number of PEs and achieves the highest possible throughput, at the expense of more hardware usage