Probability density function

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In probability theory, a probability density function (pdf), or density of a continuous random variable is a function that describes the relative likelihood for this random variable to occur at a given point. (Wikipedia.org)






Conferences related to Probability density function

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2014 American Control Conference - ACC 2014

All areas of the theory and practice of automatic control, including but not limited to network control systems, model predictive control, systems analysis in biology and medicine, hybrid and switched systems, aerospace systems, power and energy systems and control of nano- and micro-systems.

  • 2013 American Control Conference (ACC)

    Control systems theory and practice. Conference themes on sustainability, societal challenges for control, smart healthcare systems. Conference topics include biological systems, vehicle dynamics and control, consensus control, cooperative control, control of communication networks, control of networked systems, control of distributed parameter systems, decentralized control, delay systems, discrete-event systems, fault detection, fault-tolerant systems, flexible structures, flight control, formation flying, fuzzy systems, hybrid systems, system identification, iterative learning control, model predictive control, linear parameter-varying systems, linear matrix inequalities, machine learning, manufacturing systems, robotics, multi-agent systems, neural networks, nonlinear control, observers, optimal control, optimization, path planning, navigation, robust control, sensor fusion, sliding mode control, stochastic systems, switched systems, uncertain systems, game theory.

  • 2012 American Control Conference - ACC 2012

    All areas of control engineering and science.

  • 2011 American Control Conference - ACC 2011

    ACC provides a forum for bringing industry and academia together to discuss the latest developments in the area of Automatic Control Systems, from new control theories, to the advances in sensors and actuator technologies, and to new applications areas for automation.

  • 2010 American Control Conference - ACC 2010

    Theory and practice of automatic control

  • 2009 American Control Conference - ACC 2009

    The 2009 ACC technical program will cover new developments related to theory, application, and education in control science and engineering. In addition to regular technical sessions the program will also feature interactive and tutorial sessions and preconference workshops.

  • 2008 American Control Conference - ACC 2008

  • 2007 American Control Conference - ACC 2007

  • 2006 American Control Conference - ACC 2006 (Silver Anniversary)

  • 2005 American Control Conference - ACC 2005


2013 16th International Conference on Information Fusion - (FUSION 2013)

Scope of the conference is to provide medium to discuss advances and applications of fusion methodologies. Conference will include contributions in the areas of fusion methodologies, theory and representation, algorithms and modelling and simulation.

  • 2012 15th International Conference on Information Fusion (FUSION)

    The objective of the conference is to provide a forum to discuss advances and applications of fusion methodologies. The conference will feature keynote speeches, special sessions, and tutorials on topics of current interest.

  • 2011 International Conference on Information Fusion (FUSION)

    This conference is dedicated to advancing the knowledge, theory, and applications of information fusion. Topics will include radar processing, artificial intelligence, target tracking, classification, sensor networks, and sensor management.

  • 2010 13th International Conference on Information Fusion - (FUSION 2010)

    This annual conference aims to bring together professionals from around the world to facilitate discussion on the recent advances and pertinent issues in fusion technologies. Key themes are Methodologies, Algorithmic Domains, Solution Paradigms, Sensor Specific Processing and Fusion, Modelling, Simulation and Evaluation and Application Domains.

  • 2009 12th International Conference on Information Fusion - (FUSION 2009)

    Overview -- The 12th International Conference on Information Fusion will be held in Seattle, Washington, at the Grand Hyatt Seattle Hotel. Authors are invited to submit papers describing advances and applications in information fusion, with submission of non-traditional topics encouraged. Conference Site -- Pacific Northwest is one of the most scenic parts of United States and Seattle is the home of some of the world's biggest technology companies such as Boeing and Microsoft. Seattle is easily accessible

  • 2008 11th International Conference on Information Fusion - (FUSION 2008)

    The conference exists to advance the understanding of information fusion methodologies, algorithms, technologies and applications.

  • 2007 10th International Conference on Information Fusion - (FUSION 2007)

    This conference is the annual conference of the International Society of Information Fusion (ISIF:www.isif.org). It is the forum of scientists and engineers involved in sensor fusion, data fusion, information fusion and knowledge management.


2013 26th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

This is a general Electrical and Computer Engineering Conference which encompasses all aspects of these fields.

  • 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

    On behalf of the organizing committee of the 2012 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), it is with great pleasure to invite you to the 25th anniversary of this conference. CCECE is the annual flagship of IEEE Canada, and over the past 24 years it has been established as a major forum in various areas of electrical and computer engineering for researchers from Canada and around the world. The silver anniversary of CCECE in Montreal is an important milestone in the history of this conference, and the organizing committee members are trying hard to make it a memorable one.

  • 2011 24th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)

    The 2011 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2011) will be held in Niagara Falls, Ontario, Canada from May 8 11, 2011. CCECE 2011 provides a forum for the presentation of electrical and computer engineering research and development from Canada and around the world. Papers are invited, in French or English, for the following symposia.

  • 2010 IEEE 23rd Canadian Conference on Electrical and Computer Engineering - CCECE

    CCECE 2010 provides researchers, students, and practicing professionals in the area of Electrical and Computer Engineering with a Canadian venue in which they can present the latest technological advancements and discoveries. CCECE 2010 will feature papers presented from a broad range of areas in Electrical and Computer Engineering.

  • 2009 IEEE 22nd Canadian Conference on Electrical and Computer Engineering - CCECE

    CCECE provides researchers, students, and practicing professionals in the area of Electrical and Computer Engineering with a Canadian venue in which they can present the latest technological advancements and discoveries. It is also a valuable opportunity to network, exchange ideas, strengthen existing partnerships and foster new collaborations. CCECE 2009 will feature 7 mini-symposia with papers presented from a broad range of areas in Electrical and Computer Engineering. There will be tutorial sessions in

  • 2008 IEEE Canadian Conference on Electrical and Computer Engineering - CCECE

    CCECE 2008 provides a forum for the presentation of electrical and computer engineering research and development from Canada and around the world. There will be eight mini symposia and papers are invited, in French and English, including but not limited to the following topics: Biomedical Engineering, Circuits, Devices and Systems, Communications and Networking, Computer Systems and Applications, Control and Robotics, Emerging Areas, Power Electronics and Systems, Signal and Multimedia Processing.

  • 2007 Canadian Conference on Electrical and Computer Engineering - CCECE

    Brings together researchers working in all areas covered by the IEEE Technical Societies. There is a special emphasis on Communications, Power, Computers, Signal Processing, and Biomedical Engineering.

  • 2006 Canadian Conference on Electrical and Computer Engineering - CCECE


2013 ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)

The conference features two interleaved tracks, the Information Processing (IP) track, and the Sensor Platforms, Tools and Design Methods (SPOTS) track.


2013 IEEE Aerospace Conference

The international IEEE Aerospace Conference is organized to promote interdisciplinary understanding of aerospace systems, their underlying science and technology, and their applications to government and commercial endeavors. The annual, weeklong conference, set in a stimulating and thought -provoking environment, is designed for aerospace experts, academics, military personnel, and industry leaders.

  • 2012 IEEE Aerospace Conference

    The international IEEE Aerospace Conference is organized to promote interdisciplinary understanding of aerospace systems, their underlying science and technology, and their applications to government and commercial endeavors. The annual, weeklong conference, set in a stimulating and thought-provoking environment, is designed for aerospace experts, academics, military personnel, and industry leaders.

  • 2011 IEEE Aerospace Conference

    The international IEEE Aerospace Conference is organized to promote interdisciplinary understanding of aerospace systems, their underlying science and technology, and their applications to government and commercial endeavors.

  • 2010 IEEE Aerospace Conference

    The international IEEE Aerospace Conference is organized to promote interdisciplinary understanding of aerospace systems, their underlying science and technology, and their applications to government and commercial endeavors.

  • 2009 IEEE Aerospace Conference

    The international IEEE Aerospace Conference promotes interdisciplinary understanding of aerospace systems, their underlying science and technology, and their applications to government and commercial endeavors. It is an annual, week-long conference designed for aerospace experts, academics, military personnel, and industry leaders and is set in a stimulating, thought-provoking environment.


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Periodicals related to Probability density function

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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 ...


Power Systems, IEEE Transactions on

Requirements, planning, analysis, reliability, operation, and economics of electrical generating, transmission, and distribution systems for industrial, commercial, public, and domestic consumption.


Reliability, IEEE Transactions on

Principles and practices of reliability, maintainability, and product liability pertaining to electrical and electronic equipment.


Signal Processing, IEEE Transactions on

The technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital, electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of thesetechnologies.


Vehicular Technology, IEEE Transactions on

IEEE Transactions on Vehicular Technology was one of the most-cited journals, ranking number-six (tying with IEEE Communications Letters) in telecommunications in 2002, according to the annual Journal Citation Report (2002 edition) published by the Institute for Scientific Information. This periodical covers land, airborne, and maritime mobile services; portable or hand-carried and citizens' communications services, when used as an adjunct to ...



Most published Xplore authors for Probability density function

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Xplore Articles related to Probability density function

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Calculation of stochastic generation costs considering wind power generation

Kyung-Il Min; Su-Won Lee; Hongrae Kim; Young-Hyun Moon 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific, 2009

This paper represents a calculation method of stochastic generation cost (SGC) taking into consideration the wind power generation expressed as random variables, and shows its necessity. As wind power generation is stochastically predictable, a system demand should be expressed to a random variable with its own probability density function (PDF) instead of a constant value in unit commitment (UC) and ...


Efficient Computation of Normalized Maximum Likelihood Codes for Gaussian Mixture Models With Its Applications to Clustering

So Hirai; Kenji Yamanishi IEEE Transactions on Information Theory, 2013

This paper addresses the issue of estimating from a given data sequence the number of mixture components for a Gaussian mixture model(GMM). Our approach is to compute the normalized maximum likelihood (NML) code length for the data sequence relative to a GMM, then to find the mixture size that attains the minimum of the NML on the basis of the ...


Blind separation for mixtures of sub-Gaussian and super-Gaussian sources

B. -C. Ihm; D. -J. Park; Y. -H. Kwon 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2000

We propose a new intelligent blind source separation algorithm for the mixture of sub-Gaussian and super-Gaussian sources. The algorithm consists of an update equation of the separating matrix and an adjustment equation of nonlinear functions. The weighted sum of two nonlinear functions is adapted to obtain the proper nonlinear function for each source. To verify the validity of the proposed ...


A multi-scale image inpainting algorithm based on GMRF model

Rui Wang; Dongbing Gu; Guangwen Liu; Junxi Sun 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2009

A novel approach to image inpainting is introduced in this paper. The novelty lies in the combination of the MRF inpainting technique and a multiscale information fusion mechanism. This combination uses both local information via the MRF technique and global information via the multi-scale mechanism to improve the image inpainting quality. The proposed algorithm consists of three steps. In the ...


Effects of Carrier Offset on the Classification of Binary Frequency Shift Keying Based on the Product of Two Consecutive Signal Values

H. Mustafa; M. Doroslovacki 2006 40th Annual Conference on Information Sciences and Systems, 2006

In this paper we propose a feature to distinguish frequency shift keying modulation from amplitude shift keying and phase shift keying modulations in the presence of carrier offset. The feature is based on the product of two consecutive signal values and on time averaging of the imaginary part of the product. First, the conditional probability density functions of the feature ...


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Educational Resources on Probability density function

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eLearning

Calculation of stochastic generation costs considering wind power generation

Kyung-Il Min; Su-Won Lee; Hongrae Kim; Young-Hyun Moon 2009 Transmission & Distribution Conference & Exposition: Asia and Pacific, 2009

This paper represents a calculation method of stochastic generation cost (SGC) taking into consideration the wind power generation expressed as random variables, and shows its necessity. As wind power generation is stochastically predictable, a system demand should be expressed to a random variable with its own probability density function (PDF) instead of a constant value in unit commitment (UC) and ...


Efficient Computation of Normalized Maximum Likelihood Codes for Gaussian Mixture Models With Its Applications to Clustering

So Hirai; Kenji Yamanishi IEEE Transactions on Information Theory, 2013

This paper addresses the issue of estimating from a given data sequence the number of mixture components for a Gaussian mixture model(GMM). Our approach is to compute the normalized maximum likelihood (NML) code length for the data sequence relative to a GMM, then to find the mixture size that attains the minimum of the NML on the basis of the ...


Blind separation for mixtures of sub-Gaussian and super-Gaussian sources

B. -C. Ihm; D. -J. Park; Y. -H. Kwon 2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2000

We propose a new intelligent blind source separation algorithm for the mixture of sub-Gaussian and super-Gaussian sources. The algorithm consists of an update equation of the separating matrix and an adjustment equation of nonlinear functions. The weighted sum of two nonlinear functions is adapted to obtain the proper nonlinear function for each source. To verify the validity of the proposed ...


A multi-scale image inpainting algorithm based on GMRF model

Rui Wang; Dongbing Gu; Guangwen Liu; Junxi Sun 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2009

A novel approach to image inpainting is introduced in this paper. The novelty lies in the combination of the MRF inpainting technique and a multiscale information fusion mechanism. This combination uses both local information via the MRF technique and global information via the multi-scale mechanism to improve the image inpainting quality. The proposed algorithm consists of three steps. In the ...


Effects of Carrier Offset on the Classification of Binary Frequency Shift Keying Based on the Product of Two Consecutive Signal Values

H. Mustafa; M. Doroslovacki 2006 40th Annual Conference on Information Sciences and Systems, 2006

In this paper we propose a feature to distinguish frequency shift keying modulation from amplitude shift keying and phase shift keying modulations in the presence of carrier offset. The feature is based on the product of two consecutive signal values and on time averaging of the imaginary part of the product. First, the conditional probability density functions of the feature ...


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IEEE-USA E-Books

  • Random Signals

    This chapter provides an overview of integration of the Gaussian probability density function and the Q-function. It explains the weighted sum of random variables and properties of Gaussian variables. The chapter presents the central limit theorem and ensembles average, autocorrelation functions of random processes. It also explores statistical properties of additive white Gaussian noise (AWGN). The chapter provides step-by-step code exercises and instructions to implement execution sequences. The MATLAB command randn(1,b) generates a 1??b vector whose elements are realizations of independent and identically distributed Gaussian random variables with zero mean and unit variance. The chapter summarizes the analytical relationship among the input, the output, and the impulse response of a linear system in the time domain. It is designed to help teach and understand communication systems using a classroom-tested, active learning approach.

  • On nonuniform packet switched delta networks and the hotspot effect

    We analyse the performance of a multistage interconnection network (MIN) with a packet-switching protocol, embedded in a closed network of processors. First, the expected value of transmission time through a delta-2 type of MIN is determined. We then obtain, for the first time by an analytical method, a formula for its probability density function from which the variance and higher moments follow. Previously densities have only been estimated by simulation which is expensive and can be unreliable, especially in the often crucial tail region. Numerical results reveal new insights into the hot-spot phenomenon which occurs when one output address is selected more frequently than the others. We first show how mean transmission time on hot paths increases with the hot-spot intensity and compare this with cooler paths. We also plot the density functions for these transmission times. Hence it is possible to determine precisely transmission time variability and to obtain reliability measures from their tails. The approach can handle arbitrary routing frequencies to the MIN output addresses and suggests new approximation techniques with wider applicability.

  • Arrays of Point Sources

    Arranging the elements in an aperture is the critical first step in the array design process. Point sources replace real antenna elements in order to determine the element spacing, lattice, aperture shape, and number of elements that meet array performance requirements. The amplitude and phase of the electromagnetic field radiated by an isotropic point source are constant at a set instant in time and distance from the source. Aliasing occurs when the array takes less than 2 samples of the signal per period. Spatial aliasing produces large pattern lobes that steal gain from the main beam and point in directions other than the desired direction. Elements in a subarray are combined to form one signal. The Bayliss amplitude taper produces low sidelobes for different patterns. The normalized desired amplitude taper serves as a probability density function for a uniform array that is to be thinned.

  • Probability Fundamentals

    This chapter contains sections titled: Introduction Probability Density Function Common Probability Density Functions Cumulative Distribution Function Methods for Determining Probability Density Functions Problems

  • A Performance Bound for Mamoeuvring Target Tracking Using BestFitting Gaussian Distributions

    In this paper, we consider the problem of calculating the Posterior Cramér-Rao Lower Bound (PCRLB) in the case of tracking a manoeuvring target. In a recent article [1] the anthors calculated the PCRLB conditional on the manoeuvre sequence and then determined the bound as a weighted average, giving an unconditional PCRLB (referred to herein as the Enumer-PCRLB). However, we argue that this approach can produce an optimistic lower bound because the sequence of manoeuvres is implicitly assumed known. Indeed, in simulations we show that in tracking a target that can switch between a nearly constant- velocity (NCV) model and a coordinated turn (CT) model, the Enumer-PCRLB can be lower than the PCRLB in the case of tracking a target whose motion is governed purely by tbe NCV model. Motivated by this, in this paper we develop a general approach to calculating the manoeuvring target PCRLB based on utilizing best-fitting Gaussian distributions. The basis of the technique is, at each stage, to approximate the multi-modal prior target probability density function using a best-fitting Gaussian distribution. We present a recursive formula for calculating the mean and covarlanee of this Gaussian distribution, and demonstrate bow the covariance increases as a result of the potential manoeuvres. We are then able to calculate the PCRLB using a standard Riccati- like recursion. Returning to our previous example, we show that this best- fitting Gaussian approach gives a bound that shows the correct qualitative behavior, namely that the bound is greater when the target can manoeuvre. Moreover, for simulated scenarios taken from (1], we show that the best- fitting Gaussian PCRLB is both greater than the existing bound (the Enumer- PCRLB) and more consistent with the performance of the variable structure interacting multiple model (VS-IMM) tracker utilized therein.

  • Extensions to the UniformField Model

    This chapter contains sections titled: Frequency Stirring Unstirred Energy Alternative Probability Density Function Problems

  • Fractal Analysis of Heart Rate Variability

    This chapter contains sections titled: Introduction The fBm Model The Autocorrelation Function for DFGN The Probability Density Function for DFGN A Maximum Likelihood Estimator for DFGN PSD Estimators for fBm and DFGN A Wavelet Estimator for DFGN The Heart Rate Variability Signal This chapter contains sections titled: References

  • Appendix C: Probability Density Function for Amplitudes

    Up-to-date, expert coverage of topics in wireless voice communications Voice communication is the most important facet of mobile radio service. Even when the predicted surge of wireless data and Internet services becomes a reality, voice will remain the most natural means of human communication. Voice Compression and Communications details issues in wireless voice communications and treats compression, channel coding, and wireless transmission as a joint subject. Part I covers background material, whereas Part II provides detailed information on both proprietary and standardized analysis-by-synthesis codecs, including the speech codecs of virtually all existing wireline-based and wireless systems. Parts III and IV discuss mainly research-based wideband, audio, as well as very low-rate schemes likely to find their way into future standards. Voice Compression and Communications describes fundamental concepts in a non-mathematical way early in the book for those with only a background knowledge of signal processing and communications. More advanced readers will find detailed discussions of theoretical principles, future concepts, and solutions to various specific wireless voice communications problems.

  • Probability and Random Variables

    This chapter reviews uniform and Gaussian random variables (RVs). It describes the empirical probability density function (PDF) of RVs and provides its comparison with the theoretical PDF. Using MATLAB functions such as random(), rand(), and randn(), the authors generate various kinds of RVs. Although the built-in function histogram() is convenient for generating the empirical distribution, the chapter provides the detailed steps to obtain the distribution to gain an in-depth understating of the PDF concept. The MATLAB function randn, every time it is invoked, generates a sample of the Gaussian RV with zero mean and unit variance. The mean and the variance are calculated using numerical integration. The chapter also discusses Rayleigh fading model, which is one of the commonly encountered fading channel models in wireless communications. The chapter is designed to help teach and understand communication systems using a classroom-tested, active learning approach.

  • Mobility Effects In Wireless Mobile Networks

    This chapter discusses the effect of mobility on link and topology of wireless networks. A common approach for analysis of the effect of mobility on the link lifetime (LL) and residual link lifetime (RLL) of wireless networks is geometrical modeling. Using the geometric model, probability density function of LL or RLL can be obtained for simple synthetic mobility models. For analysis of the effect of mobility on topology of wireless networks, a phase transition phenomenon was observed for different scenarios for two well-known topology control protocols, homogeneous topology control and k-Neigh topology control. The authors observed that disconnection occurs suddenly in the networks rather than gradually. Another observation was that the degree of the effective topology was almost fixed around 4.5 at the disconnection time. Using these facts, one can evaluate the lifetime of the topologies which could be directly used for optimizing the hello interval in topology control protocols.



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