2 edition of Optimum reception in non-gaussian electromagnetic interference environments. found in the catalog.
Optimum reception in non-gaussian electromagnetic interference environments.
by U.S. Dept. of Commerce, National Telecommunications and Information Administration in [Washington, D.C.?]
Written in English
|Statement||D. Middleton, A.D. Spaulding.|
|Series||NTIA report -- 83-120.|
|Contributions||Spaulding, A. D., United States. National Telecommunications and Information Administration.|
|The Physical Object|
|Pagination||xv, 331 p. :|
|Number of Pages||331|
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Get this from a library. Optimum reception in non-gaussian electromagnetic interference environments. II, Optimum and suboptimum threshold signal detection in class A and B noise.
[D Middleton; A D Spaulding; United States. National Telecommunications and Information Administration.]. Optimum reception in non-gaussian electromagnetic interference environments.
II, Optimum and suboptimum A tutorial review of elements of weak signal detection in non-Gaussian EMI environments [microform] / D Urban residential man-made radio noise analysis and predictions [by] A.D.
Spaulding, W.H. Ahlbeck, [and]. Author of Optimum reception in non-gaussian electromagnetic interference environments, Effects of narrow-band filters on the output envelopes and phases of joint AM-FM inputs, Histocompatibility Testing, Effective erasure of magnetic tapes, Statistical-physical models of man-made and natural radio noise, Nursing I, Nursing 2, Toni Morrison's Fiction.
The locally optimum Bayes theory of signal detection in additive non-Gaussian noise/interference is extended to independent observations of the received data without the additive noise restriction. Middleton, D., “Multiple-Element Threshold Signal Detection of Underwater Acoustic Signals in Non-Gaussian Interference Environments.” Contractor Report NOSC CR,Naval Ocean Systems Center, San Diego, CA Google ScholarCited by: 1.
Optimum reception in non-Gaussian electromagnetic interference environments. Part 2: Optimum and suboptimum threshold signal detection in class A and B noise ArticleAuthor: Andreas Maras.
Part 2, Measurement of gated-noise interference to C-ba Measurements to determine potential interference to public safety radio receivers from ultrawideband tra Radio frequency interference handbook / Department of Communications; Optimum reception in non-gaussian electromagnetic interference environments.
II, Optimum and suboptimum. done  - on designing the optimum detector for digital data transmission systems in the presence of interference, but most of the effort has been devoted to the case of Gaussian interference.
In this case the solutions for both coherent and incoherent reception schemes have been well analyzed and the. Abstract. Procedures for the detection of both weak and narrowband signals in non–Gaussian noise environments are discussed.
For the weak signal case, nonlinear processors based on the Middleton Class A noise model and the mixture representation are by: 2. Progress In Electromagnetics Research,P –, NON-LINEAR INTERFERENCE CANCELLATION TECHNIQUES FOR ELECTROMAGNETICALLY DENSE PROPAGATION ENVIRONMENTS performances in non-Gaussian environments.
Higher Order Statistics (HOS)  is a powerful means for characterizing and modelling non-Gaussian noise, and building efficient and robust signal detectors on the basis of this complete noise analysis. In this work, a new method for detecting signals in.
Except for the strong interference regime, the sum-capacity of the G-IC is known exactly only for the Z-channel and in the noisy interference regime, the latter deﬁned by q I S (1 + I) 1 2 in the symmetric case, for which i.i.d. Gaussian inputs in (2) are optimal . So, instead of pursuing exact results, theAuthor: Alex Dytso, Daniela Tuninetti, Natasha Devroye.
gaussian and non-gaussian environments and application to STAP. Chin Yuan Chong To cite this version: Chin Yuan Chong. Signal processing for MIMO radars: detection under gaussian and non-gaussian environments and application to STAP.
Other. Supélec, English. NNT: SUPL. tel. size fractional lower-order moment algorithm for non-Gaussian interference environ-ments,” has been submitted to Elsevier Digital Signal Processing, Dec.
Paper 4, Y. Zheng and T. Shao, “A Variable Step-Size LMP Algorithm for Heavy-Tailed Interference Suppression in Phased Array Radar,” has been published. Statisticaltheory of EMC 78Nl ton, New York, NY: Threshold signal and parameter estimation in non-Gaussian EMC environments.
7gN2 ing, NTIA, Boulder, CO: Locally optimum and sub-optimum detector performance in non-Gaussian "broadband" and "narrowband interference environments. ovich, Electrotechnical 5/5(1). Full text of "DTIC ADA Electromagnetic Noise Interference and Compatibility" See other formats. IEEE Non-Gaussian Statistical Communication Theory.
The book is based on the observation that communication is the central operation of discovery in all the sciences. In its "active mode" we use it to "interrogate" the physical world, sending appropriate "signals" and receiving nature's "reply". IEEE TRANSACTIONS ON INFORMATION THEORY, VOL.
IT, NO. 2, MARCH Detectors for Discrete-Time Signals in Non-Gaussian Noise JAMES H. MILLER, STUDENT MEMBER. optimum detector and with the fully optimum detector for correlated Gaussian noise is made.
1 Introduction The synthesis and the performance analysis of detection al-gorithms optimized against non-Gaussian noise are generally very difﬁcult.
Therefore, to obtain detection structures of easy implementation, some simplifying assumptions about. To verify the effectiveness of the proposed control method given in Fig. 3, a simulation test was carried out by an aluminum cantilever parameters of the beam are listed in Table 1 and the locations of the excitation (input) and control (output) points are shown in Fig.
ingly, the amplitude-frequency diagrams of Frequency Response Functions (FRFs) of the system are exhibited Cited by: 6. electromagnetic noise is classified according to its source – atmospheric or man-made noise. It is common to apply the recommendation ITU-R P for estimating the environmental character of background noise.
The recommendation defines five typical environments in the context of RF (Radio Frequency) reception.8.a.4 "The problem of optimum detection of discrete information in the presence of normal and Non-Gaussian Noise", Radio Engineering and Electronic Physics, N 1,pp 8.a.5 "Detection Algorithms of signals in Markov noise with unknown statistics", Radio Engineering and Electronic Physics, N 6,pp Signal processing is an essential topic for all practicing and aspiring electrical engineers to understand no matter what specific area they are involved in.
Originally published by McGraw-Hill* and now reissued by Artech House, this definitive volume offers a unified, comprehensive and practical treatment of statistical and adaptive signal processing.