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About 10,000 papers for “Probability of error”

Probability of Undetected Error of

Marco Baldi, Franco Chiaraluce, Kløve Fellow Ieee · 2007

Computation of the undetected error probability for error correcting codes over the Z-channel is an important issue, explored only in part in previous literature. In this paper we consider the case of Varshamov-Tenengol’ts codes, by presenting some analytical, numerical, and heuristic methods for unveiling this additional feature. Possible comparisons with Hamming codes are also shown and discussed.

Cited by 0

The Effect of Phase Error on DPSK Error Probability

Nelson M. Blachman · IRE Transactions on Communications Systems · 1981

Expressions are found for the effect of an error in the delay of the preceding signal, which provides the reference phase for the decoding of the present signal in differential phase-shift-keying reception. The signal-to-noise ratio is allowed to be different for the two signals that are compared by the receiver's phase detector. The results are applicable to both binary and quaternary DPSK. In addition, an approximation is obtained for the error probability when the two Signal-to-noise ratios are equal to the same large value.

Cited by 61

Minimum Probability of Error Image Retrieval

Nuno Vasconcelos · IEEE Transactions on Signal Processing · 2004

We address the design of optimal architectures for image retrieval from large databases. Minimum probability of error (MPE) is adopted as the optimality criterion and retrieval formulated as a problem of statistical classification. The probability of retrieval error is lower- and upper-bounded by functions of the Bayes and density estimation errors, and the impact of the components of the retrieval architecture (namely, the feature transformation and density estimation) on these bounds is characterized. This characterization suggests interpreting the search for the MPE feature set as the search for the minimum of the convex hull of a collection of curves of probability of error versus feature space dimension. A new algorithm for MPE feature design, based on a dictionary of empirical feature sets and the wrapper model for feature selection, is proposed. It is shown that, unlike traditional feature selection techniques, this algorithm scales to problems containing large numbers of classes. Experimental evaluation reveals that the MPE architecture is at least as good as popular empirical solutions on the narrow domains where these perform best but significantly outperforms them outside these domains.

Cited by 69

Minimum Probability of Error Signal Representation

Jorge F. Silva, Shrikanth Narayanan · Machine learning for signal processing ... · 2007

The problem of minimum probability of error signal representation (MPE-SR) considering issues of finite training data is revisited and extended in this paper. Results are presented that justify addressing this problem as a complexity-regularized optimization criterion, reflecting the well-known tradeoff between signal representation quality and learning complexity. A rate-distortion type of formulation is proposed to address this optimization problem by finding a sequence of signal representations achieving optimal complexity-fidelity operational points. Finally under specific assumptions, it is shown that the MPE-SR reduces to a version of Fisher linear discriminant analysis.

Cited by 8

Probability Theory of Bit Error Rate

2009

This chapter contains sections titled: Introduction Bit Error Ratio and Bit Error Rate Definitions OSNR and Spectral Matching Carrier-to-Noise Ratio Shannon's Limit Optical Signal-to-Noise Ratio Probability and Statistics 101 Bit Error Probability Bit Error Contributors Bit Error Rate Optical Signal-to-Noise Ratio Channel Capacity and SNR The Quality or Q-Factor Bit Error Monitoring BER and Data Patterning BER and Eye Diagram Eye-Pattern Mask References Standards

Cited by 2

Error Probability of Distributed Arithmetic Coding

Yong Fang, Nan Yang, Jun Chen · IEEE Communications Letters · 2021

Distributed Arithmetic Coding (DAC) is an interesting realization of Slepian-Wolf coding that performs nonlinear coset-like partition for equiprobable binary sources. Just as in other coding problems, it is a very important issue to theoretically predict the decoding error probability of DAC. This letter proposes a plausible solution to this difficult issue. Our analyses are based on the concept of coexisting interval introduced in our previous work. Specifically, we use it to deduce the probability that two given codewords coexist in the same coset. Experimental results confirm the correctness of our theoretical analyses.

Cited by 1

Average error exponent of undetected error probability of binary matrix ensembles

Kazushi Mimura, Tadashi Wadayama, Toshiyuki Tanaka et al. · 2011

We evaluate average error exponent of the undetected error probability of binary matrix ensembles by applying statistical-mechanics approach, which is called the “quenched” average error exponent. In the exixting analysis, the “annealed” average error exponent, which is the error exponent of the average undetected error probability, has been evaluated. The quenched average error exponent is more suitable to capture typical behaviors. We show that there are some cases where the annealed exponent is overestimated for the irregular sparse matrix ensemble. We also show that the quenched average error exponent is equivalent to the annealed average error exponents for the regular sparse matrix ensemble.

Cited by 0

The Probability Distribution of Conditional Classification Error

Josef Kittler, Pierre A. Devijver · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1980

The probability distribution of the error incurred by a classification system on a given data set is derived. It is shown that the distribution is mixed binomial. A method for calculating the mixed binomial distribution recursively is proposed.

Cited by 4

Computation of the circular error probability integral

J. Gillis · IEEE Transactions on Aerospace and Electronic Systems · 1991

The author describes a simplified derivation of the representation of the circular error probability (CEP) integral, which is the integral over a disk centered at the origin of a zero mean two-dimensional Gaussian random variable, as a one-dimensional integral. In addition, two series are presented which can be used to compute efficiently the CEP integral. The domain of applicability of the series and methods for acceleration of the convergence of these series are discussed. The integral occurs in the evaluation of communication and radar signals, and in other statistical applications.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 28

The Probability and Statistics of Human Error

2006

Can we predict accidents? In all engineering systems that humans invented anduse, errors and accidents occur. The errors are recorded as outcomes (failures, accidents, deaths, events, injuries, losses, and the like) and are the subject of investigation for the assignment of cause and blame, and of fiscal, corporate and personal liability and responsibility. They can themselves cause expensive inquiries, regulations, and litigation. Almost invariably, the major contribution to the cause of failure is from human error within the engineering system and its operational control functions. It arises from interactions within the entire homo-technological system, of which the human is just a part, but a vital part.

Cited by 0

Renyi's entropy and the probability of error

Moshe Ben-Bassat, J. Raviv · IEEE Transactions on Information Theory · 1978

The basic properties of Renyi's entropy are reviewed, and its concavity properties are characterized. New bounds (referred to as <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I_{\alpha}</tex> bounds) on the probability of error are derived from Renyi's entropy and are compared with known bounds. It is proved that for the two-class case, the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I_{2}</tex> bound is sharper than many of the previously known bounds. The difference between the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I_{2}</tex> bound and the real value of the probability of error is at most 0.09.

Cited by 101

Digital processing of touch signal - error probability

Zoran Milivojević, Milena J. Stanojlović Mirković, Mihajlo Stefanović · EUROCON'2001. International Conference on Trends in Communications. Technical Program, Proceedings (Cat. No.01EX439) · 2002

A new algorithm for digital processing of a touch signal is proposed. We consider the calculation of the error probability in the process of deciding on the existence of the optical infrared beam between the infrared transmitter and receiver. The error probability is calculated in the function of: (a) the ambient illumination simulated by the reflector placed a certain distance in front of the center of the touch interface; (b) window functions implemented in the algorithm for processing of the touch signal. The error probability is calculated for some classical, time-symmetrical as well as for some original, time-asymmetrical window functions.

Cited by 0

SADIK TRANSFORM OF ERROR FUNCTION (PROBABILITY INTEGRAL)

Sudhanshu Aggarwal*1 & Swarg Deep Sharma2 · Zenodo (CERN European Organization for Nuclear Research) · 2019

The solutions of many advanced engineering problems like Fick’s second law, heat and mass transfer problems, vibrating beams problems contains error and complementary error function. When we use any integral transform to solve these types of problems, it is very necessary to know the integral transform of error function. In this article, we find the Sadik transform of error and complementary error functions. To demonstrate the usefulness of Sadik transform of error function, some numerical applications are considered in application section for solving improper integrals which contain error function. It is pointed out that Sadik transform give the exact solution of improper integral which contains error function without any tedious calculation work.

Cited by 0Open access