White noise

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White noise is a random signal (or process) with a flat power spectral density. (Wikipedia.org)






Conferences related to White noise

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2017 IEEE/MTT-S International Microwave Symposium - IMS 2017

The IEEE MTT-S International Microwave Symposium (IMS) is the premier conference covering basic technologies, to passives and actives components to system over a wide range of frequencies including VHF, UHF, RF, microwave, millimeter-wave, terahertz, and optical. The conference will encompass the latest in RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation, wireless systems, RFID and related topics.

  • 2029 IEEE/MTT-S International Microwave Symposium - MTT 2029

    The IEEE International Microwave Symposium (IMS) is the world s foremost conference covering the UHF, RF, wireless, microwave, millimeter-wave, terahertz, and optical frequencies; encompassing everything from basic technologies to components to systems including the latest RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation and more. The IMS includes technical and interactive sessions, exhibits, student competitions, panels, workshops, tutorials, and networking events.

  • 2021 IEEE/MTT-S International Microwave Symposium - IMS 2021

    The IEEE MTT-S International Microwave Symposium (IMS) is the premier conference covering basic technologies, to passives and actives components to system over a wide range of frequencies including VHF, UHF, RF, microwave, millimeter-wave, terahertz, and optical. The conference will encompass the latest in RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation, wireless systems, RFID and related topics.

  • 2019 IEEE/MTT-S International Microwave Symposium - MTT 2019

    Comprehensive symposium on microwave theory and techniques including active and passive circuit components, theory and microwave systems.

  • 2018 IEEE/MTT-S International Microwave Symposium - MTT 2018

    Microwave theory and techniques, RF/microwave/millimeter-wave/terahertz circuit design and fabrication technology, radio/wireless communication.

  • 2016 IEEE/MTT-S International Microwave Symposium - IMS 2016

    The IEEE International Microwave Symposium (IMS) is the world s foremost conference covering the UHF, RF, wireless, microwave, millimeter-wave, terahertz, and optical frequencies; encompassing everything from basic technologies to components to systems including the latest RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation and more. The IMS includes technical and interactive sessions, exhibits, student competitions, panels, workshops, tutorials, and networking events.

  • 2015 IEEE/MTT-S International Microwave Symposium - MTT 2015

    The IEEE MTT-S International Microwave Symposium (IMS) is the premier conference covering basic technologies, to passives and actives components to system over a wide range of frequencies including VHF, UHF, RF, microwave, millimeter-wave, terahertz, and optical. The conference will encompass the latest in RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation, wireless systems, RFID and related topics. The IMS includes technical sessions, both oral and interactive, worksh

  • 2014 IEEE/MTT-S International Microwave Symposium - MTT 2014

    IMS2014 will cover developments in microwave technology from nano devices to system applications. Technical paper sessions, interactive forums, plenary and panel sessions, workshops, short courses, industrial exhibits, and a wide array of other technical activities will be offered.

  • 2013 IEEE/MTT-S International Microwave Symposium - MTT 2013

    The IEEE MTT-S International Microwave Symposium (IMS) is the premier conference covering basic technologies, to passives and actives components to system over a wide range of frequencies including VHF, UHF, RF, microwave, millimeter -wave, terahertz, and optical. The conference will encompass the latest in RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation, wireless systems, RFID and related topics.The IMS includes technical and interactive sessions, exhibits, student competitions, panels, workshops, tutorials, and networking events.

  • 2012 IEEE/MTT-S International Microwave Symposium - MTT 2012

    The IEEE International Microwave Symposium (IMS) is the world s foremost conference covering the UHF, RF, wireless, microwave, millimeter-wave, terahertz, and optical frequencies; encompassing everything from basic technologies to components to systems including the latest RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation and more. The IMS includes technical and interactive sessions, exhibits, student competitions, panels, workshops, tutorials, and networking events.

  • 2011 IEEE/MTT-S International Microwave Symposium - MTT 2011

    The IEEE International Microwave Symposium (IMS) is the world s foremost conference covering the UHF, RF, wireless, microwave, millimeter-wave, terahertz, and optical frequencies; encompassing everything from basic technologies to components to systems including the latest RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation and more. The IMS includes technical and interactive sessions, exhibits, student competitions, panels, workshops, tutorials, and networking events.

  • 2010 IEEE/MTT-S International Microwave Symposium - MTT 2010

    Reports of research and development at the state-of-the-art of the theory and techniques related to the technology and applications of devices, components, circuits, modules and systems in the RF, microwave, millimeter-wave, submillimeter-wave and Terahertz ranges of the electromagnetic spectrum.

  • 2009 IEEE/MTT-S International Microwave Symposium - MTT 2009

    The IEEE International Microwave Symposium (IMS) is the world s foremost conference covering the UHF, RF, wireless, microwave, millimeter-wave, terahertz, and optical frequencies; encompassing everything from basic technologies to components to systems including the latest RFIC, MIC, MEMS and filter technologies, advances in CAD, modeling, EM simulation and more. The IMS includes technical and interactive sessions, exhibits, student competitions, panels, workshops, tutorials, and networking events.

  • 2008 IEEE/MTT-S International Microwave Symposium - MTT 2008

  • 2007 IEEE/MTT-S International Microwave Symposium - MTT 2007


2012 24th Chinese Control and Decision Conference (CCDC)

Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2011 23rd Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2010 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies


2011 9th IEEE International Conference on Control and Automation (ICCA)

IEEE ICCA 2001 aims to create a forum for scientists and practicing engineers throughout the world to present the latest research findings and ideas in the areas of control and automation.



Periodicals related to White noise

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Circuits and Systems I: Regular Papers, IEEE Transactions on

Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.


Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on

Methods, algorithms, and human-machine interfaces for physical and logical design, including: planning, synthesis, partitioning, modeling, simulation, layout, verification, testing, and documentation of integrated-circuit and systems designs of all complexities. Practical applications of aids resulting in producible analog, digital, optical, or microwave integrated circuits are emphasized.


Lightwave Technology, Journal of

All aspects of optical guided-wave science, technology, and engineering in the areas of fiber and cable technologies; active and passive guided-wave componentry (light sources, detectors, repeaters, switches, fiber sensors, etc.); integrated optics and optoelectronics; systems and subsystems; new applications; and unique field trials.


Microwave Theory and Techniques, IEEE Transactions on

Microwave theory, techniques, and applications as they relate to components, devices, circuits, and systems involving the generation, transmission, and detection of microwaves.



Most published Xplore authors for White noise

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Xplore Articles related to White noise

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Cough sound discrimination in noisy environments using microphone array

Payam Moradshahi; Hanieh Chatrzarrin; Rafik Goubran 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2013

Cough sound discriminator algorithms are capable of distinguishing between dry and wet cough types. The performance of such algorithms, however, is affected by noise and reverberation in the environment. The effect of reverberation on the performance of cough sound discriminators was previously studied in [1]. In this paper, the effect of noise on the performance of cough sound discriminator is ...


The effect of space diversity on coded modulation for the fading channel

J. Ventura-Traveset; G. Caire; E. Biglieri Proceedings of 1995 IEEE International Symposium on Information Theory, 1995

We address the problem of designing a coded modulation scheme for the fading channel when space diversity is used. We focus on the fact that a channel affected by fading can be asymptotically turned into an additive white Gaussian noise (AWGN) channel by increasing the number of diversity branches, thus turning coded-modulation schemes designed for the AWGN channel into efficient ...


Estimation of close sinusoids in colored noise and model discrimination

C. Chatterjee; R. Kashyap; G. Boray IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987

This paper considers the estimation of the two close dominant frequencies in the signal when it is known a priori that the observation is a sum of two close sinusoids and an additive colored noise whose spectral density is unknown. Earlier attempts have assumed the additive noise to be independent. Next we develop decision rules for checking whether the observed ...


Systematic Luby Transform Codes and Their Soft Decoding

T. D. Nguyen; L. L. Yang; L. Hanzo 2007 IEEE Workshop on Signal Processing Systems, 2007

Luby Transform codes (LT) were originally designed for the Binary Erasure Channel (BEC) encountered owing to randomly dropped packets in the statistical multiplexing aided classic wireline-based Internet, where transmitted packets are not affected by the fading or noise of the propagation environment of the wireless Internet. For the sake of transmitting data over the BEC routinely encountered in statistical multiplexing ...


A Novel Parameter-Tuned Stochastic Resonator for Binary PAM Signal Processing at Low SNR

Jin Liu; Zan Li; Lei Guan; Lei Pan IEEE Communications Letters, 2014

To improve the receiving performance of binary pulse amplitude modulated (BPAM) signal at low signal-to-noise ratio (SNR), a novel parameter-tuned stochastic resonator (PSR) is proposed. In this letter, we propose a new method for PSR which combines the conventional stochastic resonance (SR) approach based on classic adiabatic approximation theory with the non- conventional SR approach based on parameter tuned theory. ...


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Educational Resources on White noise

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eLearning

Cough sound discrimination in noisy environments using microphone array

Payam Moradshahi; Hanieh Chatrzarrin; Rafik Goubran 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2013

Cough sound discriminator algorithms are capable of distinguishing between dry and wet cough types. The performance of such algorithms, however, is affected by noise and reverberation in the environment. The effect of reverberation on the performance of cough sound discriminators was previously studied in [1]. In this paper, the effect of noise on the performance of cough sound discriminator is ...


The effect of space diversity on coded modulation for the fading channel

J. Ventura-Traveset; G. Caire; E. Biglieri Proceedings of 1995 IEEE International Symposium on Information Theory, 1995

We address the problem of designing a coded modulation scheme for the fading channel when space diversity is used. We focus on the fact that a channel affected by fading can be asymptotically turned into an additive white Gaussian noise (AWGN) channel by increasing the number of diversity branches, thus turning coded-modulation schemes designed for the AWGN channel into efficient ...


Estimation of close sinusoids in colored noise and model discrimination

C. Chatterjee; R. Kashyap; G. Boray IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987

This paper considers the estimation of the two close dominant frequencies in the signal when it is known a priori that the observation is a sum of two close sinusoids and an additive colored noise whose spectral density is unknown. Earlier attempts have assumed the additive noise to be independent. Next we develop decision rules for checking whether the observed ...


Systematic Luby Transform Codes and Their Soft Decoding

T. D. Nguyen; L. L. Yang; L. Hanzo 2007 IEEE Workshop on Signal Processing Systems, 2007

Luby Transform codes (LT) were originally designed for the Binary Erasure Channel (BEC) encountered owing to randomly dropped packets in the statistical multiplexing aided classic wireline-based Internet, where transmitted packets are not affected by the fading or noise of the propagation environment of the wireless Internet. For the sake of transmitting data over the BEC routinely encountered in statistical multiplexing ...


A Novel Parameter-Tuned Stochastic Resonator for Binary PAM Signal Processing at Low SNR

Jin Liu; Zan Li; Lei Guan; Lei Pan IEEE Communications Letters, 2014

To improve the receiving performance of binary pulse amplitude modulated (BPAM) signal at low signal-to-noise ratio (SNR), a novel parameter-tuned stochastic resonator (PSR) is proposed. In this letter, we propose a new method for PSR which combines the conventional stochastic resonance (SR) approach based on classic adiabatic approximation theory with the non- conventional SR approach based on parameter tuned theory. ...


More eLearning Resources

IEEE.tv Videos

An Analysis of Phase Noise Requirements for Ultra-Low-Power FSK Radios: RFIC Interactive Forum 2017
Tutorial of Shlomo Engelberg on use of noise to make measurements
IMS 2011 Microapps - A Comparison of Noise Parameter Measurement Techniques
Noise Enhanced Information Systems: Denoising Noisy Signals with Noise
IEEE Innovation Day 2011-Innovation Day Keynote Address
IMS 2011 Microapps - Ultra Low Phase Noise Measurement Technique Using Innovative Optical Delay Lines
APEC Speaker Highlights: Robert White, Chief Engineer, Embedded Power
ISEC 2013 Special Gordon Donaldson Session: Remembering Gordon Donaldson - 7 of 7 - SQUID-based noise thermometers for sub-Kelvin thermometry
IMS 2012 Microapps - Phase Noise Choices in Signal Generation: Understanding Needs and Tradeoffs Riadh Said, Agilent
A Transformer-Based Inverted Complementary Cross-Coupled VCO with a 193.3dBc/Hz FoM and 13kHz 1/f3 Noise Corner: RFIC Interactive Forum
A 40GHz PLL with -92.5dBc/Hz In-Band Phase Noise and 104fs-RMS-Jitter: RFIC Interactive Forum 2017
MicroApps: Phase Noise, Allan Variance, and Frequency Reference (Agilent Technologies)
A Low Power High Performance PLL with Temperature Compensated VCO in 65nm CMOS: RFIC Interactive Forum
MicroApps: Recent Improvement on Y-Factor Noise Figure Measurement Uncertainty (Agilent Technologies)
Where's my electric car?
MicroApps: Anatomy of PXI (National Instruments)
Summary and Next Steps - Internet Inclusion: Global Connect Stakeholders Advancing Solutions, Washington DC, 2016
MicroApps: Impairment Calibration in Quadrature Systems (National Instruments)
2013 IEEE & RSE Wolfson James Clerk Maxwell Award
Day Two Opening Remarks by Megan Smith - Internet Inclusion: Global Connect Stakeholders Advancing Solutions, Washington DC, 2016

IEEE-USA E-Books

  • Reduction of Quantizing Noise by Use of FeedbackReceived June 25, 1962. This paper is based in part on n dissertation by H. Austin Spung, III for the degree of Doctor of Engineering in the Yale Sehool of Enginccring. The dissertation was supported by Bell Telephone Laborntories, Murray Hill, N. J

    Many information transmission systems use a discrete (digital) channel. Since most input signals are continuous, the conversion cannot be accomplished without an error which, for many cases, may be considered to have the characteristics of white noise. A method has been suggested to reduce this error by using linear feedback around the quantizer to shape the noise spectrum. Each output sample will then contain not only signal information but also information about the errors in the previous samples. Such a system is analyzed for random input signals of a rather general nature. Under assumptions allowing essentially no clipping in the quantizer and setting an upper bound on the coherence between samples of the input signal, the system can be represented by a simple model. A comparison is made of the mean-square error with and without feedback. It is shown that considerable reduction in noise power can be obtained by a slight increase in sampling rate. For example, an increase of 25 per cent in the sampling rate provides a 95 per cent decrease in error-noise power. This is equivalent to having about two additional bits per sample in the transmission channel.

  • Bibliography

    Although state variable concepts are a part of modern control theory, they have not been extensively applied in communication theory. The purpose of this book is to demonstrate how the concepts and methods of state variables can be used advantageously in analyzing a variety of communication theory problems. In contrast to the impulse response and covariance function description of systems and random processes commonly used in the analysis of communication problems, Professor Baggeroer points out that a state variable approach describes these systems and processes in terms of differential equations and their excitation, which is usually a white-noise process. Theoretically, such a description provides a very general characterization on which a large class of systems, possibly time varying and nonlinear, can be modeled. Practically, the state variable approach often provides a more representative physical description of the actual dynamics of the systems involved and, most importantly, can lead to solution techniques that are readily implemented on a computer and that yield specific numerical results.The work focuses on how state variables can be used to solve several of the integral equations that recur in communication theory including, for example, the Kahunen-Loeve theorem, the detection of a known signal in the presence of a colored noise, and the Wiener-Hopf equation. The book is divided into two parts. The first part deals with the development from first principles of the state variable solution techniques for homogeneous and inhomogeneous Fredholm integral solutions. The second part considers two specific applications of the author's integral equation theory: to optimal signal design for colored noise channels, and to linear estimation theory.The main thrust o f the material presented in this book is toward finding effective numerical procedures for analyzing complex problems. Professor Baggeroer has combined several different mathematical tools not commonly used together to attack the detection and signal design problems. Numerous examples are presented throughout the book to emphasize the numerical aspects of the author's methods. If the reader is familiar with detection and estimation theory and with deterministic state variable concepts, the ideas, techniques, and results contained in this work will prove highly relevant, if not directly applicable, to a large number of communication theory problems.MIT Research Monograph No. 61

  • High¿¿¿Order Delta¿¿¿Sigma Modulators

    This chapter discusses high¿¿¿order delta¿¿¿sigma modulators and examines how the quantizer is overloaded even for small inputs, reducing its effective gain and thereby resulting in instability. The expression for in¿¿¿band noise was based on the assumption that quantization can be modeled as a uniformly distributed, additive, white¿¿¿noise source. The effect of saturation can be separated from the process of quantization by thinking of the saturating quantizer as a cascade of a saturating nonlinearity following a quantizer with an infinite range. The Bode sensitivity integral gives us a different kind of insight into why using a high¿¿¿order Noise Transfer Function (NTF) is more effective in reducing in¿¿¿band quantization noise. One can reduce the number of quantizer levels, while increasing the sampling rate equivalent to operating at a higher oversampling ratio (OSR) or by increasing the order of noise¿¿¿shaping. The loop¿¿¿filter consists of a cascade of three delaying integrators, with the quantizer output fed back into each of the integrators with different weight factors.

  • Some Lower Bounds on Signal Parameter Estimation

    New bounds are presented for the maximum accuracy with which parameters of signals imbedded in white noise can be estimated. The bounds are derived by comparing the estimation problem with related optimal detection problems. They are, with few exceptions, independent of the bias and include explicitly the dependence on the a priori interval. The new results are compared with previously known results.

  • Equalizers

    This chapter discusses equalizers for single-carrier transmission in wireless systems. We first set up a time-discrete model for the channel, filters, and equalizer. A noise-whitening filter or precursor equalizer ensures white noise at the equalizer input. Transmit filter, channel, matched filter, and noise whitening filter can be modeled together by an equivalent time-discrete channel. We then turn to the various types of equalizers. Linear equalizers consist of linear filters, usually tapped delay lines (though IIR filters and lattice filters are also possible), whose coefficients are optimized according to certain criteria. Zero-forcing equalizers eliminate intersymbol interference, but lead to noise enhancement, while minimum mean square error (MMSE) equalizers trade off these error sources. Adaptation algorithms for the coefficients trade off complexity, convergence rate, and misadjustment. Example algorithms include the least mean square (LMS) algorithm (stochastic gradient method), the recursive least squares algorithm (RLS), or direct computation of the Wiener filter. Decision feedback equalizer (DFE) consist of a feedforward filters and a feedback filter that eliminates the postcursor impact. DFEs generally perform well, but must avoid error propagation. The best performance is obtained by maximum-likelihood sequence estimators (MLSE) or Viterbi equalizers. They act similar to Viterbi decoders for convolutional codes, since the channel can be interpreted as a rate-1 convolutional encoder. Finally, we discuss blind equalizers, which do not require a training sequence for detection. Certain signal properties, e.g., constant envelope, finite symbol alphabet, cyclostationarity, or spectral correlation, can be used to separate the effect of the channel on the received signal from the signal modulation, and perform implicit equalization. The best-known algorithms are the constant-modulus algorithm (CMA), blind MLSE, and algorithms using higher- order statistics.

  • Computation of the Exponential Matrix

    Although state variable concepts are a part of modern control theory, they have not been extensively applied in communication theory. The purpose of this book is to demonstrate how the concepts and methods of state variables can be used advantageously in analyzing a variety of communication theory problems. In contrast to the impulse response and covariance function description of systems and random processes commonly used in the analysis of communication problems, Professor Baggeroer points out that a state variable approach describes these systems and processes in terms of differential equations and their excitation, which is usually a white-noise process. Theoretically, such a description provides a very general characterization on which a large class of systems, possibly time varying and nonlinear, can be modeled. Practically, the state variable approach often provides a more representative physical description of the actual dynamics of the systems involved and, most importantly, can lead to solution techniques that are readily implemented on a computer and that yield specific numerical results.The work focuses on how state variables can be used to solve several of the integral equations that recur in communication theory including, for example, the Kahunen-Loeve theorem, the detection of a known signal in the presence of a colored noise, and the Wiener-Hopf equation. The book is divided into two parts. The first part deals with the development from first principles of the state variable solution techniques for homogeneous and inhomogeneous Fredholm integral solutions. The second part considers two specific applications of the author's integral equation theory: to optimal signal design for colored noise channels, and to linear estimation theory.The main thrust o f the material presented in this book is toward finding effective numerical procedures for analyzing complex problems. Professor Baggeroer has combined several different mathematical tools not commonly used together to attack the detection and signal design problems. Numerous examples are presented throughout the book to emphasize the numerical aspects of the author's methods. If the reader is familiar with detection and estimation theory and with deterministic state variable concepts, the ideas, techniques, and results contained in this work will prove highly relevant, if not directly applicable, to a large number of communication theory problems.MIT Research Monograph No. 61

  • Noise and Frequency Stability

    This chapter contains sections titled: White Noise Colored Noises Small and Band Limited Perturbations of Sinusoidal Signals Statistical Approach Power Spectra of Stochastic Processes

  • Name Index

    Although state variable concepts are a part of modern control theory, they have not been extensively applied in communication theory. The purpose of this book is to demonstrate how the concepts and methods of state variables can be used advantageously in analyzing a variety of communication theory problems. In contrast to the impulse response and covariance function description of systems and random processes commonly used in the analysis of communication problems, Professor Baggeroer points out that a state variable approach describes these systems and processes in terms of differential equations and their excitation, which is usually a white-noise process. Theoretically, such a description provides a very general characterization on which a large class of systems, possibly time varying and nonlinear, can be modeled. Practically, the state variable approach often provides a more representative physical description of the actual dynamics of the systems involved and, most importantly, can lead to solution techniques that are readily implemented on a computer and that yield specific numerical results.The work focuses on how state variables can be used to solve several of the integral equations that recur in communication theory including, for example, the Kahunen-Loeve theorem, the detection of a known signal in the presence of a colored noise, and the Wiener-Hopf equation. The book is divided into two parts. The first part deals with the development from first principles of the state variable solution techniques for homogeneous and inhomogeneous Fredholm integral solutions. The second part considers two specific applications of the author's integral equation theory: to optimal signal design for colored noise channels, and to linear estimation theory.The main thrust o f the material presented in this book is toward finding effective numerical procedures for analyzing complex problems. Professor Baggeroer has combined several different mathematical tools not commonly used together to attack the detection and signal design problems. Numerous examples are presented throughout the book to emphasize the numerical aspects of the author's methods. If the reader is familiar with detection and estimation theory and with deterministic state variable concepts, the ideas, techniques, and results contained in this work will prove highly relevant, if not directly applicable, to a large number of communication theory problems.MIT Research Monograph No. 61

  • Quantization Noise Spectra

    Uniform qunntizers play a fundamental role in digital communication systems and have been the subject of extensive study for many decades, The inherent nonlinearity of quantizers makes their analysis hoth difficult and Interesting, It usually has been accomplished either by assuming the quantizer noise to be a signal-independent, uniform white random process or by replacing the quantizer by a deterministic linear device, or by combining the two assumptions. Such linearizing approximations simplify the analysis and permit the use of linear systems techniques, but few results exist quantifying how good such approximations are for specific systems, These complications are magnified when the quantizer is inside a feedback loop, as for Sigma-Delta modulators. Exact descriptions of the moments and spectra of quantizer noise have been developed recently for the special case of single-loop, multistage and multiloop Signul-Delta modulators. These results demonstrate. that the white noise and linearization assumptions can be quite poor approximations in some systems and quite good in others. It turns out that many of the techniques used in the analysis were first applied to the analysis of quantizers by Clavier, Panter, and Grieg (1947) in pioneering (but often overlooked) work that preceded Bennett's (1948) classic study of quantization noise spectra. We take advantage of the benefit of hindsight to develop several results describing the behavior of quantization noise in a unified and simplified manner. Exact formulas for quantizer noise spectra are developed and applied to a variety of systems and inputs, including scalar quantization (PCM), dithered PCM, Sigma-Delta modulation, dithered Sigma-Delta modulation, two-stage Sigma-Delta modulation, and second-order Sigma-Delta modulation.

  • Appendix II: Gaussian White Noise

    A practical approach to obtaining nonlinear dynamic models from stimulus- response data Nonlinear modeling of physiological systems from stimulus-response data is a long-standing problem that has substantial implications for many scientific fields and associated technologies. These disciplines include biomedical engineering, signal processing, neural networks, medical imaging, and robotics and automation. Addressing the needs of a broad spectrum of scientific and engineering researchers, this book presents practicable, yet mathematically rigorous methodologies for constructing dynamic models of physiological systems. Nonlinear Dynamic Modeling of Physiological Systems provides the most comprehensive treatment of the subject to date. Starting with the mathematical background upon which these methodologies are built, the book presents the methodologies that have been developed and used over the past thirty years. The text discusses implementation and computational issues and gives il ustrative examples using both synthetic and experimental data. The author discusses the various modeling approaches–nonparametric, including the Volterra and Wiener models; parametric; modular; and connectionist–and clearly identifies their comparative advantages and disadvantages along with the key criteria that must guide successful practical application. Selected applications covered include neural and sensory systems, cardiovascular and renal systems, and endocrine and metabolic systems. This lucid and comprehensive text is a valuable reference and guide for the community of scientists and engineers who wish to develop and apply the skills of nonlinear modeling to physiological systems.



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