On the Detection of a Known Signal in a Non‐Gaussian Noise Process

1968 ◽  
Vol 44 (1) ◽  
pp. 141-147 ◽  
Author(s):  
Ronald L. Spooner
Keyword(s):  
Gaussian Noise ◽  
Noise Process ◽  
Non Gaussian

scholarly journals Bounds on the Sum-Rate of MIMO Causal Source Coding Systems with Memory under Spatio-Temporal Distortion Constraints

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 842
Author(s):  
Photios A. Stavrou ◽  
Jan Østergaard ◽  
Mikael Skoglund
Keyword(s):  
Gaussian Noise ◽  
Rate Distortion ◽  
Source Model ◽  
Upper Bounds ◽  
Optimal Test ◽  
Test Channel ◽  
Noise Process ◽  
Channel Realization ◽  
Spatio Temporal ◽  
Non Gaussian

In this paper, we derive lower and upper bounds on the OPTA of a two-user multi-input multi-output (MIMO) causal encoding and causal decoding problem. Each user’s source model is described by a multidimensional Markov source driven by additive i.i.d. noise process subject to three classes of spatio-temporal distortion constraints. To characterize the lower bounds, we use state augmentation techniques and a data processing theorem, which recovers a variant of rate distortion function as an information measure known in the literature as nonanticipatory ϵ-entropy, sequential or nonanticipative RDF. We derive lower bound characterizations for a system driven by an i.i.d. Gaussian noise process, which we solve using the SDP algorithm for all three classes of distortion constraints. We obtain closed form solutions when the system’s noise is possibly non-Gaussian for both users and when only one of the users is described by a source model driven by a Gaussian noise process. To obtain the upper bounds, we use the best linear forward test channel realization that corresponds to the optimal test channel realization when the system is driven by a Gaussian noise process and apply a sequential causal DPCM-based scheme with a feedback loop followed by a scaled ECDQ scheme that leads to upper bounds with certain performance guarantees. Then, we use the linear forward test channel as a benchmark to obtain upper bounds on the OPTA, when the system is driven by an additive i.i.d. non-Gaussian noise process. We support our framework with various simulation studies.

STATEMENT OF THE PROBLEM ON SYNTHESIS OF OPTIMAL EVALUATION OF SIGNAL PARAMETERS IN NON-GAUSSIAN NOISE

2012 ◽  
Vol 71 (17) ◽  
pp. 1541-1555
Author(s):  
V. A. Baranov ◽  
S. V. Baranov ◽  
A. V. Nozdrachev ◽  
A. A. Rogov
Keyword(s):  
Gaussian Noise ◽  
Signal Parameters ◽  
Non Gaussian ◽  
Optimal Evaluation

NONPARAMETRIC DECODING OF BLOCK CODES IN CHANNELS WITH NON-GAUSSIAN NOISE

2013 ◽  
Vol 72 (11) ◽  
pp. 1029-1038
Author(s):  
M. Yu. Konyshev ◽  
S. V. Shinakov ◽  
A. V. Pankratov ◽  
S. V. Baranov
Keyword(s):  
Gaussian Noise ◽  
Block Codes ◽  
Non Gaussian

Wavelet threshold algorithm analysis under non-Gaussian noise background

2013 ◽  
Vol 32 (9) ◽  
pp. 2445-2447
Author(s):  
Qing-hua LI ◽  
Dalabaev Senbai ◽  
Xin-jian QIU ◽  
Chang LIAO ◽  
Quan-fu SUN
Keyword(s):  
Gaussian Noise ◽  
Algorithm Analysis ◽  
Noise Background ◽  
Threshold Algorithm ◽  
Non Gaussian
Sign in / Sign up

Export Citation Format

Share Document