scholarly journals Speech Signal Recovery in Communication Networks

10.14311/542 ◽  
2004 ◽  
Vol 44 (2) ◽  
Author(s):  
V. Zagursky ◽  
A. Riekstinsh
Keyword(s):  
Communication Networks ◽  
Speech Signal ◽  
Standard Procedure ◽  
Second Order ◽  
Signal Recovery ◽  
Packet Losses ◽  
Communications Networks ◽  
Adaptive Interpolation ◽  
Source Signal ◽  
Correlation Properties

Interpolation approaches to the shape recovery of a speech signal in transmission over packet switched communications networks are proposed. The samples of signal fragments are mixed and transmitted in correspondence with standard procedure for packet-switched transmission. After reception a reverse permutation is made. In the case of packet losses missing samples are separated by several samples of the source signal. Correlation properties of the signal are used for the recovery samples due to first- and second-order non-adaptive and adaptive interpolation. For the loss of 25 % packets and second order adaptive interpolation a 2- 4 % error distribution range has been achieved.

Speech Signal Recovery Using Block Sparse Bayesian Learning

2019 ◽  
Vol 45 (3) ◽  
pp. 1567-1579
Author(s):  
Irfan Ahmed ◽  
Aftab Khan ◽  
Nasir Ahmad ◽  
NasruMinallah ◽  
Hazrat Ali
Keyword(s):  
Speech Signal ◽  
Bayesian Learning ◽  
Signal Recovery ◽  
Sparse Bayesian Learning

scholarly journals Sparse Signal Recovery for Direction-of-Arrival Estimation Based on Source Signal Subspace

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Bo Lin ◽  
Jiying Liu ◽  
Meihua Xie ◽  
Jubo Zhu
Keyword(s):  
Computational Cost ◽  
Real Data ◽  
Direction Of Arrival ◽  
Sparse Signal ◽  
Sparse Signal Recovery ◽  
Signal Recovery ◽  
Signal Subspace ◽  
Second Order Cone ◽  
Source Signal ◽  
Improved Accuracy

After establishing the sparse representation of the source signal subspace, we propose a new method to estimate the direction of arrival (DOA) by solving anℓ1-norm minimization for sparse signal recovery of the source powers. Second-order cone programming is applied to reformulate this optimization problem, and it is solved effectively by employing the interior point method. Due to the keeping of the signal subspace and the discarding of the noise subspace, the proposed method is more robust to noise than many other sparsity-based methods. The real data tests and the numerical simulations demonstrate that the proposed method has improved accuracy and robustness to noise, and it is not sensitive to the knowledge about the number of sources. We discuss the computational cost of our method theoretically, and the experiment results verify the computational effectiveness.

The Gas Turbine Test Facility in the Information Age

2000 ◽  
Author(s):  
Grant T. Patterson ◽  
C. Edward Dorman ◽  
W. R. Sloan
Keyword(s):  
Gas Turbine ◽  
Communication Networks ◽  
Test Data ◽  
Rapid Expansion ◽  
Test Facility ◽  
Web Based ◽  
Communications Networks ◽  
Storage Devices ◽  
Customer Base ◽  
Security Network

The Arnold Engineering Development Center (AEDC) must supply test data and test results to a geographically diverse customer base. The rapid expansion of communications technology has reshaped the landscape of how this data and information are transmitted to gas turbine manufacturers whose products are tested at AEDC. This paper will discuss the development of the communication networks for the transmittal of engine test data and information in near real-time. Past, present and future communication capabilities will be discussed. Topics will include the communication networks, the communication protocol, transmission security, network infrastructure, computers and storage devices of the overall data management and transmission system. Finally the AEDC Integrated Test Information System (ITIS) will be discussed. ITIS takes advantage of the latest technologies in communications networks, web-based communication, information/data fusion and the archiving of test data, metadata and information.

scholarly journals Consensus Analysis of Second-Order Multi-Agent Networks With Sampled Data and Packet Losses

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 8127-8137 ◽  
Author(s):  
Wenxia Cui ◽  
Yang Tang ◽  
Jian-An Fang ◽  
Jurgen Kurths
Keyword(s):  
Second Order ◽  
Sampled Data ◽  
Packet Losses ◽  
Consensus Analysis ◽  
Multi Agent ◽  
Agent Networks

scholarly journals Requirements of EU law enforcement agencies for lawful interception of information in electronic communications networks

2021 ◽  
pp. 115-120
Author(s):  
S. КOKIZA ◽  
V. STEPANOV
Keyword(s):  
Law Enforcement ◽  
Communication Networks ◽  
Electronic Communication ◽  
Eu Law ◽  
Law Enforcement Agencies ◽  
Electronic Communications ◽  
Communications Networks ◽  
Normative Documents ◽  
Lawful Interception ◽  
The Eu

The article is devoted to the analysis of regulatory and legal acts and normative documents of the EU on information interception in electronic communication networks in the context of preparation of technical regulations of the united system of technical means.

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