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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2019 IEEE 20th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)

For its 20th year edition, the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) 2019, returns to the country that saw its birth, France. Held in Cannes, in the heart of the world renown “French Riviera” (Cote d’Azur in French), the SPAWC 2019 will exhibit a technical program complete with high profile plenaries, invited and contributed papers, all appearing under IEEE explore. A flagship workshop of the IEEE SP Society SPCOM technical committee, SPAWC 2019 will combine cutting edge research in the fields of signal processing, statistical learning, communication theory, wireless networking and more, together with an exciting social program on the glamorous and sunny Riviera.

2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA)

Industrial Informatics, Computational Intelligence, Control and Systems, Cyber-physicalSystems, Energy and Environment, Mechatronics, Power Electronics, Signal and InformationProcessing, Network and Communication Technologies

2018 14th IEEE International Conference on Signal Processing (ICSP)

ICSP2018 includes sessions on all aspects of theory, design and applications of signal processing. Prospective authors are invited to propose papers in any of the following areas, but not limited to: A. Digital Signal Processing (DSP)B. Spectrum Estimation & ModelingC. TF Spectrum Analysis & WaveletD. Higher Order Spectral AnalysisE. Adaptive Filtering &SPF. Array Signal ProcessingG. Hardware Implementation for Signal ProcessingH Speech and Audio CodingI. Speech Synthesis & RecognitionJ. Image Processing & UnderstandingK. PDE for Image ProcessingL.Video compression &StreamingM. Computer Vision & VRN. Multimedia & Human-computer InteractionO. Statistic Learning & Pattern RecognitionP. AI & Neural NetworksQ. Communication Signal processingR. SP for Internet and Wireless CommunicationsS. Biometrics & AuthentificationT. SP for Bio-medical & Cognitive ScienceU

2018 19th International Conference of Young Specialists on Micro/Nanotechnologies and Electron Devices (EDM)

EDM 2018 is a significant event aimed at development of scientific schools working on foreground areas of Russian science and technology. The main areas are research, design and implementation of micro/nanostructures, radio and telecommunication devices, power electronicand mechatronic systems which are now related to the development of scientific and technological progress. The conference aims to gather young specialists of the differentuniversities of Russia, CIS and other countries. Invited Russian and foreign specialists will report about the development of science and technologies, perspectives of further development of modern electronics. This conference is focused primarily on the discussion of the fundamental theoretical and technological problems of designing and implementing products of micro- and nanoelectronics, simulation methods, and engineering experiments and physical interpretation of the results of these experiments.

2018 25th IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE Signal Processing Society, is the premier forum for the presentation of technological advances and research results in the fields of theoretical, experimental, and applied image and video processing. ICIP 2018, the 25th in the series that has been held annually since 1994, brings together leading engineers and scientists in image and video processing from around the world.

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Periodicals related to White noise

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Applied Superconductivity, IEEE Transactions on

Contains articles on the applications and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Power applications include magnet design as well asmotors, generators, and power transmission

Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...

Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...

Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.

Broadcasting, IEEE Transactions on

Broadcast technology, including devices, equipment, techniques, and systems related to broadcast technology, including the production, distribution, transmission, and propagation aspects.

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Most published Xplore authors for White noise

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Xplore Articles related to White noise

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Data and rate adaptive quantization for joint image denoising and compression

[{u'author_order': 1, u'affiliation': u'Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada', u'full_name': u'N. Gupta'}, {u'author_order': 2, u'affiliation': u'Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada', u'full_name': u'E. Plotkin'}, {u'author_order': 3, u'affiliation': u'Dept. of Electr. & Comput. Eng., Concordia Univ., Montreal, Que., Canada', u'full_name': u'M. N. S. Swamy'}] The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, None

The techniques proposed for joint denoising and compression of images corrupted with additive white Gaussian noise are mostly based on Rissanen's minimum description length principle and tend to operate at a particular point (or a set of points) on the rate-distortion curve. These offer some compression along with denoising, but not a practical encoding solution. This paper suggests a simple ...

Noise Detection and Reduction for Image Sensor by Time Domain Autocorrelation Function Method

[{u'author_order': 1, u'affiliation': u'Imaging System Development Section, Sony Corporation, 1-11-1 Osaki, Shinagawa-ku, Tokyo, Japan. Email: kazuhiro.hoshino@jp.sony.com', u'full_name': u'Kazuhiro Hoshino'}, {u'author_order': 2, u'affiliation': u'Imaging System Development Section, Sony Corporation, 1-11-1 Osaki, Shinagawa-ku, Tokyo, Japan', u'full_name': u'Hirofumi Sumi'}, {u'author_order': 3, u'affiliation': u'Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsuku, Kitakyushu, Fukuoka, Japan. Email: tosi-hiro@waseda.jp', u'full_name': u'Toshihiro Nishimura'}] 2007 IEEE International Symposium on Industrial Electronics, None

The present paper describes noise detection and reduction for an imaging system by a method of autocorrelation of pixel data change as a function of time. The random noise level could be detected for each pixel using the proposed method. An algorithm proposed for determining the noise level, and calculating the pixel value by the autocorrelation function value reduced the ...

Image segmentation using factor graphs

[{u'author_order': 1, u'affiliation': u'Coordinated Sci. Lab., Illinois Univ., Urbana-Champaign, IL, USA', u'full_name': u'R. J. Drost'}, {u'author_order': 2, u'affiliation': u'Coordinated Sci. Lab., Illinois Univ., Urbana-Champaign, IL, USA', u'full_name': u'A. C. Singer'}] IEEE Workshop on Statistical Signal Processing, 2003, None

Factor graphs were first studied in the context of error correction decoding and have since been shown to be a useful tool in a wide variety of applications. In this paper, we provide a brief introduction to factor graphs with an emphasis on their broad applicability, and then describe a new algorithm for segmenting binary images that have been blurred ...

Noise Analysis of Time Variant Shapers in Frequency Domain

[{u'author_order': 1, u'affiliation': u'Department of ECM, ICC of the University of Barcelona', u'full_name': u'David Gascon'}, {u'author_order': 2, u'affiliation': u'University of Balearic Islands, Campus Mateu Orfila, Mallorca, Spain', u'full_name': u'Sebasti\xe0 Bota'}, {u'author_order': 3, u'affiliation': u'Department of Electronics, ICC of the University of Barcelona, Barcelona, Spain', u'full_name': u'Angel Dieguez'}, {u'author_order': 4, u'affiliation': u'Department of ECM, ICC of the University of Barcelona', u'full_name': u'Lluis Garrido'}, {u'author_order': 5, u'affiliation': u'Department of ECM, ICC of the University of Barcelona', u'full_name': u'Eduardo Picatoste'}] IEEE Transactions on Nuclear Science, 2011

In this paper we discuss the noise analysis of time variant shapers in the frequency domain, based on well established concepts of the theory of time varying circuits. A frequency domain extension of the techniques typically adopted for noise analysis in detector instrumentation is proposed and applied to a classic time variant shaper: the gated integrator. In some cases, this ...

Incremental Gaussian elimination decoding of raptor codes over BEC

[{u'author_order': 1, u'affiliation': u'Member', u'full_name': u'Saejoon Kim'}, {u'author_order': 2, u'full_name': u'Karam Ko'}, {u'author_order': 3, u'affiliation': u'Senior Member', u'full_name': u'Sae-Young Chung'}] IEEE Communications Letters, 2008

In this letter, we investigate an efficient Gaussian elimination decoding scheme of Raptor codes used over the binary erasure channel. It will be shown that the proposed incremental Gaussian elimination decoding significantly improves on the decoding time over the usual Gaussian elimination decoding while maintaining the same decoding performance.

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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
IMS 2012 Special Sessions: The Evolution of Some Key Active and Passive Microwave Components - E. C. Niehenke
A Transformer-Based Inverted Complementary Cross-Coupled VCO with a 193.3dBc/Hz FoM and 13kHz 1/f3 Noise Corner: RFIC Interactive Forum
MicroApps: Phase Noise, Allan Variance, and Frequency Reference (Agilent Technologies)
A 40GHz PLL with -92.5dBc/Hz In-Band Phase Noise and 104fs-RMS-Jitter: RFIC Interactive Forum 2017
IMS 2014: A 600 GHz Low-Noise Amplifier Module
Compact 75 GHz LNA with 20-dB Gain and 4-dB Noise Figure - Woorim Shin - RFIC Showcase 2018
Impact of Linearity and Write Noise of Analog Resistive Memory: IEEE Rebooting Computing 2017
A Low Power High Performance PLL with Temperature Compensated VCO in 65nm CMOS: RFIC Interactive Forum
Transistors for THz Systems
MicroApps: Recent Improvement on Y-Factor Noise Figure Measurement Uncertainty (Agilent Technologies)
IMS 2014: LNA Modules for the WR4 (170-260 GHz) Frequency Range


  • Correlator Output SNR, Effective C/N0, and I/S

    The combination of signals, noise, and interference at the receiver input affects correlator output signal-to-noise ratio (SNR), an important measure of receiver performance. This chapter describes the concept of correlator output SNR and defines it rigorously, leading to the important concepts of effective C/N0 and processing gain. It discusses the severity of an interference environment in terms of the interference power-to-signal power ratio, or I/S and also describes the conversion between effective C/N0 and I/S. The resulting tools can then be extended and applied to assess the effects of multiple access interference (MAI) from a given constellation, and even from a number of constellations. Correlator output SNR is the primary metric used to assess receiver performance in interference, and expressions for correlator output. Spectral separation coefficients (SSCs) are a powerful tool for assessing the effect of interference on correlator output SNR.

  • Basics

    This chapter contains sections titled: Noise: Definition, Modeling, Properties Signal: Definition, Modeling, Properties Classification: Suppression, Cancellation, Enhancement Sampling and Quantization Audio Processing in the Frequency Domain Bandwidth Limiting Signal‐to‐Noise‐Ratio: Definition and Measurement Subjective Quality Measurement Other Methods for Quality and Enhancement Measurement Summary Bibliography

  • Noise of Building Elements

    This chapter contains sections titled: * Resistors * Inductances * Capacitance * Semiconductors * Amplifiers * Mixers * Frequency Dividers * Frequency Multipliers

  • Spectrum Sensing: Basic Techniques

    This chapter contains sections titled: Challenges Energy Detection: No Prior Information about Deterministic or Stochastic Signal Spectrum Sensing Exploiting Second‐Order Statistics Statistical Pattern Recognition: Exploiting Prior Information about Signal through Machine Learning Feature Template Matching Cyclostationary Detection

  • Introduction to Modulators: Basic Concepts and Fundamentals

    This chapter is conceived as an introduction to CMOS Sigma-Delta (?>?>) analog-to-digital converters (ADCs). Their operation principle consists in combining oversampling, quantization error processing, and negative feedback for improving the effective resolution of a coarse quantizer. Before presenting practical topologies for the implementation of ?>?> modulation, the large variety of the existing ?>?> realizations is briefly classified according to the type of modulator architecture (single loops or cascades), the circuit techniques employed (discrete time (DT) or continuous-time (CT)), and the nature of the signals being converted (low pass (LP) or band pass (BP)). Starting from the case of DT, LP, single-bit ?>?> modulators, the implications of these different alternatives are then presented in an incremental way.

  • Introduction

    This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book explores how should efficient signal coding work when very narrow bandwidths per bit are available. Communication transmits messages through time and space. In communication engineering, sending a symbol has three basic costs: energy, bandwidth, and implementation complexity. Coding, bandwidth, and their interaction lie at the heart of this book. The book is about efficient transmission via coding when the relative bandwidth is narrow. Most modulators in use today are pulse modulators, meaning that they associate each symbol with a pulse. The chapter also discusses spectra of modulated signals and the error performance and optimum receivers. Not all modulations produce simple pulses and the need to reduce bandwidth can lead to rather complicated signals. It can be a subtle exercise to distinguish coding from modulation, especially when bandwidth plays a role.

  • 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

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