Download or read book Reconstruction Methods for Periodic Non uniformly Sampled Signals written by Liang Jian Zhao and published by . This book was released on 2004 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Digital Processing and Reconstruction of Complex Signals written by Predrag B. Petrovic and published by Springer Science & Business Media. This book was released on 2010-03-21 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: In real electronic systems, voltage and current signals are not necessarily of a periodical quantity, due to the presence of nonharmonic components or/and possible stochastic variation. This book presents in three parts methods for analyzing and processing and reconstructing complex signals. The first part of this book is dedicated to the problem of measurements of the basic electric quantities in electric utilities, both from the aspect of accuracy of this type of measurements and the possibilities of simple and practical realization. The second part presents a reconstruction of trigonometric polynomials, a specific class of band-limited signals, from a number of integrated values of input signals. The third part deals with the problem of estimating the value of the active power of the ac signal in the presence of subharmonics and interharmonics. The analysis makes use of the most general model of the voltage and current signal, i.e. the most complex spectral content that can be expected to appear in practice.
Download or read book SIGNAL RECONSTRUCTION FROM NONUNIFORM SAMPLES written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Sampling and reconstruction is used as a fundamental signal processing operation since the history of signal theory. Classically uniform sampling is treated so that the resulting mathematics is simple. However there are various instances that nonuniform sampling and reconstruction of signals from their nonuniform samples are required. There exist two broad classes of reconstruction methods. They are the reconstruction according to a deterministic, and according to a stochastic model. In this thesis, the most fundamental aspects of nonuniform sampling and reconstruction, according to a deterministic model, is analyzed, implemented and tested by considering specific nonuniform reconstruction algorithms. Accuracy of reconstruction, computational efficiency and noise stability are the three criteria that nonuniform reconstruction algorithms are tested for. Specifically, four classical closed form interpolation algorithms proposed by Yen are discussed and implemented. These algorithms are tested, according to the proposed criteria, in a variety of conditions in order to identify their performances for reconstruction quality and robustness to noise and signal conditions. Furthermore, a filter bank approach is discussed for the interpolation from nonuniform samples in a computationally efficient manner. This approach is implemented and the efficiency as well as resulting filter characteristics is observed. In addition to Yen's classical algorithms, a trade off algorithm, which claims to find an optimal balance between reconstruction accuracy and noise stability is analyzed and simulated for comparison between all discussed interpolators. At the end of the stability tests, Yen's third algorithm, known as the classical recurrent nonuniform sampling, is found to be superior over the remaining interpolators, from both an accuracy and stability point of view.
Download or read book Signal Reconstruction Algorithms for Time Interleaved ADCs written by Anu Kalidas Muralidharan Pillai and published by Linköping University Electronic Press. This book was released on 2015-05-22 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: An analog-to-digital converter (ADC) is a key component in many electronic systems. It is used to convert analog signals to the equivalent digital form. The conversion involves sampling which is the process of converting a continuous-time signal to a sequence of discrete-time samples, and quantization in which each sampled value is represented using a finite number of bits. The sampling rate and the effective resolution (number of bits) are two key ADC performance metrics. Today, ADCs form a major bottleneck in many applications like communication systems since it is difficult to simultaneously achieve high sampling rate and high resolution. Among the various ADC architectures, the time-interleaved analog-to-digital converter (TI-ADC) has emerged as a popular choice for achieving very high sampling rates and resolutions. At the principle level, by interleaving the outputs of M identical channel ADCs, a TI-ADC could achieve the same resolution as that of a channel ADC but with M times higher bandwidth. However, in practice, mismatches between the channel ADCs result in a nonuniformly sampled signal at the output of a TI-ADC which reduces the achievable resolution. Often, in TIADC implementations, digital reconstructors are used to recover the uniform-grid samples from the nonuniformly sampled signal at the output of the TI-ADC. Since such reconstructors operate at the TI-ADC output rate, reducing the number of computations required per corrected output sample helps to reduce the power consumed by the TI-ADC. Also, as the mismatch parameters change occasionally, the reconstructor should support online reconfiguration with minimal or no redesign. Further, it is advantageous to have reconstruction schemes that require fewer coefficient updates during reconfiguration. In this thesis, we focus on reducing the design and implementation complexities of nonrecursive finite-length impulse response (FIR) reconstructors. We propose efficient reconstruction schemes for three classes of nonuniformly sampled signals that can occur at the output of TI-ADCs. Firstly, we consider a class of nonuniformly sampled signals that occur as a result of static timing mismatch errors or due to channel mismatches in TI-ADCs. For this type of nonuniformly sampled signals, we propose three reconstructors which utilize a two-rate approach to derive the corresponding single-rate structure. The two-rate based reconstructors move part of the complexity to a symmetric filter and also simplifies the reconstruction problem. The complexity reduction stems from the fact that half of the impulse response coefficients of the symmetric filter are equal to zero and that, compared to the original reconstruction problem, the simplified problem requires only a simpler reconstructor. Next, we consider the class of nonuniformly sampled signals that occur when a TI-ADC is used for sub-Nyquist cyclic nonuniform sampling (CNUS) of sparse multi-band signals. Sub-Nyquist sampling utilizes the sparsities in the analog signal to sample the signal at a lower rate. However, the reduced sampling rate comes at the cost of additional digital signal processing that is needed to reconstruct the uniform-grid sequence from the sub-Nyquist sampled sequence obtained via CNUS. The existing reconstruction scheme is computationally intensive and time consuming and offsets the gains obtained from the reduced sampling rate. Also, in applications where the band locations of the sparse multi-band signal can change from time to time, the reconstructor should support online reconfigurability. Here, we propose a reconstruction scheme that reduces the computational complexity of the reconstructor and at the same time, simplifies the online reconfigurability of the reconstructor. Finally, we consider a class of nonuniformly sampled signals which occur at the output of TI-ADCs that use some of the input sampling instants for sampling a known calibration signal. The samples corresponding to the calibration signal are used for estimating the channel mismatch parameters. In such TI-ADCs, nonuniform sampling is due to the mismatches between the channel ADCs and due to the missing input samples corresponding to the sampling instants reserved for the calibration signal. We propose three reconstruction schemes for such nonuniformly sampled signals and show using design examples that, compared to a previous solution, the proposed schemes require substantially lower computational complexity.
Download or read book Nonuniform Sampling written by Farokh Marvasti and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 938 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our understanding of nature is often through nonuniform observations in space or time. In space, one normally observes the important features of an object, such as edges. The less important features are interpolated. History is a collection of important events that are nonuniformly spaced in time. Historians infer between events (interpolation) and politicians and stock market analysts forecast the future from past and present events (extrapolation). The 20 chapters of Nonuniform Sampling: Theory and Practice contain contributions by leading researchers in nonuniform and Shannon sampling, zero crossing, and interpolation theory. Its practical applications include NMR, seismology, speech and image coding, modulation and coding, optimal content, array processing, and digital filter design. It has a tutorial outlook for practising engineers and advanced students in science, engineering, and mathematics. It is also a useful reference for scientists and engineers working in the areas of medical imaging, geophysics, astronomy, biomedical engineering, computer graphics, digital filter design, speech and video processing, and phased array radar.
Download or read book Modern Sampling Theory written by John J. Benedetto and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: A state-of-the-art edited survey covering all aspects of sampling theory. Theory, methods and applications are discussed in authoritative expositions ranging from multi-dimensional signal analysis to wavelet transforms. The book is an essential up-to-date resource.
Download or read book Proceedings of the UNIfied Conference of DAMAS IncoME and TEPEN Conferences UNIfied 2023 written by Andrew D. Ball and published by Springer Nature. This book was released on with total page 1219 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Periodic Signals Reconstruction of Undersampled written by Anthony Joseph Silva and published by . This book was released on 1986 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Under certain conditions, a periodic signal of unknown fundamental frequency can still be recovered when sampled below the Nyquist rate, or twice the highest frequency present in the waveform. A new sampling criterion has been proposed which enumerates such conditions. It has been shown that in theory, if the signal and sampling frequencies are not integrally related, and the signal is band-limited (to a range the extent of which is known but otherwise unrestricted), then the signal waveshape can always be recovered. If the fundamental frequency is known to lie within a range not spanning any multiple of half the sampling rate, then the temporal scaling for the reconstructed waveform can be determined uniquely, as well. Procedures have also been proposed for reducing time-scale ambiguity when the latter condition is not met. A previously presented time domain algorithm for reconstructing aliased periodic signals has been implemented and modified. A new algorithm, operating in the frequency domain, has been proposed and implemented. In the new algorithm, the signal fundamental frequency is first estimated from the discrete Fourier transform of the aliased data through an iterative procedure. This estimate is then used to sort the aliased harmonics.
Download or read book Sparse representation of visual data for compression and compressed sensing written by Ehsan Miandji and published by Linköping University Electronic Press. This book was released on 2018-11-23 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ongoing advances in computational photography have introduced a range of new imaging techniques for capturing multidimensional visual data such as light fields, BRDFs, BTFs, and more. A key challenge inherent to such imaging techniques is the large amount of high dimensional visual data that is produced, often requiring GBs, or even TBs, of storage. Moreover, the utilization of these datasets in real time applications poses many difficulties due to the large memory footprint. Furthermore, the acquisition of large-scale visual data is very challenging and expensive in most cases. This thesis makes several contributions with regards to acquisition, compression, and real time rendering of high dimensional visual data in computer graphics and imaging applications. Contributions of this thesis reside on the strong foundation of sparse representations. Numerous applications are presented that utilize sparse representations for compression and compressed sensing of visual data. Specifically, we present a single sensor light field camera design, a compressive rendering method, a real time precomputed photorealistic rendering technique, light field (video) compression and real time rendering, compressive BRDF capture, and more. Another key contribution of this thesis is a general framework for compression and compressed sensing of visual data, regardless of the dimensionality. As a result, any type of discrete visual data with arbitrary dimensionality can be captured, compressed, and rendered in real time. This thesis makes two theoretical contributions. In particular, uniqueness conditions for recovering a sparse signal under an ensemble of multidimensional dictionaries is presented. The theoretical results discussed here are useful for designing efficient capturing devices for multidimensional visual data. Moreover, we derive the probability of successful recovery of a noisy sparse signal using OMP, one of the most widely used algorithms for solving compressed sensing problems.
Download or read book Wavelets written by John J. Benedetto and published by CRC Press. This book was released on 2021-07-28 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wavelets is a carefully organized and edited collection of extended survey papers addressing key topics in the mathematical foundations and applications of wavelet theory. The first part of the book is devoted to the fundamentals of wavelet analysis. The construction of wavelet bases and the fast computation of the wavelet transform in both continuous and discrete settings is covered. The theory of frames, dilation equations, and local Fourier bases are also presented. The second part of the book discusses applications in signal analysis, while the third part covers operator analysis and partial differential equations. Each chapter in these sections provides an up-to-date introduction to such topics as sampling theory, probability and statistics, compression, numerical analysis, turbulence, operator theory, and harmonic analysis. The book is ideal for a general scientific and engineering audience, yet it is mathematically precise. It will be an especially useful reference for harmonic analysts, partial differential equation researchers, signal processing engineers, numerical analysts, fluids researchers, and applied mathematicians.
Download or read book Handbook of Fourier Analysis Its Applications written by Robert J. Marks and published by Oxford University Press. This book was released on 2009-01-08 with total page 799 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical, applications-based professional handbook comprehensively covers the theory and applications of Fourier Analysis, spanning topics from engineering mathematics, signal processing and related multidimensional transform theory, and quantum physics to elementary deterministic finance and even the foundations of western music theory.
Download or read book Sampling Theory written by Yonina C. Eldar and published by Cambridge University Press. This book was released on 2015-04-09 with total page 837 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to sampling for engineers, covering the fundamental mathematical underpinnings together with practical engineering principles and applications.
Download or read book Sampling in Digital Signal Processing and Control written by Arie Feuer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Undoubtably one of the key factors influencing recent technology has been the advent of high speed computational tools. Virtually every advanced engi neering system we come in contact with these days depends upon some form of sampling and digital signal processing. Well known examples are digital tele phone systems, digital recording of audio signals and computer control. These developments have been matched by the appearance of a plethora of books which explain a variety of analysis, synthesis and design tools applica ble to sampled-data systems. The reader might therefore wonder what is distinc tive about the current book. Our observation of the existing literature is that the underlying continuous-time system is usually forgotten once the samples are tak en. The alternative point of view, adopted in this book, is to formulate the analy sis in such a way that the user is constantly reminded of the presence of the under lying continuous-time signals. We thus give emphasis to two aspects of sampled-data analysis: Firstly, we formulate the various algorithms so that the appropriate contin uous-time case is approached as the sampling rate increases. Secondly we place emphasis on the continuous-time output response rath er than simply focusing on the sampled response.
Download or read book Computational Science ICCS 2007 written by Yong Shi and published by Springer Science & Business Media. This book was released on 2007-05-18 with total page 1310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation The four-volume set LNCS 4487-4490 constitutes the refereed proceedings of the 7th International Conference on Computational Science, ICCS 2007, held in Beijing, China in May 2007. More than 2400 submissions were made to the main conference and its 35 topical workshops. The 80 revised full papers and 11 revised short papers of the main track were carefully reviewed and selected from 360 submissions and are presented together with 624 accepted workshop papers in four volumes. According to the ICCS 2007 theme "Advancing Science and Society through Computation" the papers cover a large volume of topics in computational science and related areas, from multiscale physics, to wireless networks, and from graph theory to tools for program development. The papers are arranged in topical sections on efficient data management, parallel monte carlo algorithms, simulation of multiphysics multiscale systems, dynamic data driven application systems, computer graphics and geometric modeling, computer algebra systems, computational chemistry, computational approaches and techniques in bioinformatics, computational finance and business intelligence, geocomputation, high-level parallel programming, networks theory and applications, collective intelligence for semantic and knowledge grid, collaborative and cooperative environments, tools for program development and analysis in CS, intelligent agents in computing systems, CS in software engineering, computational linguistics in HCI, internet computing in science and engineering, workflow systems in e-science, graph theoretic algorithms and applications in cs, teaching CS, high performance data mining, mining text, semi-structured, Web, or multimedia data, computational methods in energy economics, risk analysis, advances in computational geomechanics and geophysics, meta-synthesis and complex systems, scientific computing in electronics engineering, wireless and mobile systems, high performance networked media and services, evolution toward next generation internet, real time systems and adaptive applications, evolutionary algorithms and evolvable systems.
Download or read book Analysis and Recovery of Undersampled Periodic Waveforms written by Mark Christopher Miller and published by . This book was released on 1987 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Sampling Theory in Fourier and Signal Analysis Advanced Topics written by J. R. Higgins and published by Oxford University Press. This book was released on 1999-11-25 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume 1 in this series laid the mathematical foundations of sampling theory; Volume 2 surveys the many applications of the theory both within mathematics and in other areas of science. Topics range over a wide variety of areas, and each application is given a modern treatment.
Download or read book Sampling and Quantization for Optimal Reconstruction written by Shay Maymon and published by . This book was released on 2011 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis develops several approaches for signal sampling and reconstruction given different assumptions about the signal, the type of errors that occur, and the information available about the signal. The thesis first considers the effects of quantization in the environment of interleaved, oversampled multi-channel measurements with the potential of different quantization step size in each channel and varied timing offsets between channels. Considering sampling together with quantization in the digital representation of the continuous-time signal is shown to be advantageous. With uniform quantization and equal quantizer step size in each channel, the effective overall signal-to-noise ratio in the reconstructed output is shown to be maximized when the timing offsets between channels are identical, resulting in uniform sampling when the channels are interleaved. However, with different levels of accuracy in each channel, the choice of identical timing offsets between channels is in general not optimal, with better results often achievable with varied timing offsets corresponding to recurrent nonuniform sampling when the channels are interleaved. Similarly, it is shown that with varied timing offsets, equal quantization step size in each channel is in general not optimal, and a higher signal-to-quantization-noise ratio is often achievable with different levels of accuracy in the quantizers in different channels. Another aspect of this thesis considers nonuniform sampling in which the sampling grid is modeled as a perturbation of a uniform grid. Perfect reconstruction from these nonuniform samples is in general computationally difficult; as an alternative, this work presents a class of approximate reconstruction methods based on the use of time-invariant lowpass filtering, i.e., sinc interpolation. When the average sampling rate is less than the Nyquist rate, i.e., in sub-Nyquist sampling, the artifacts produced when these reconstruction methods are applied to the nonuniform samples can be preferable in certain applications to the aliasing artifacts, which occur in uniform sampling. The thesis also explores various approaches to avoiding aliasing in sampling. These approaches exploit additional information about the signal apart from its bandwidth and suggest using alternative pre-processing instead of the traditional linear time-invariant anti-aliasing filtering prior to sampling.
