Combustion Parameters Estimation Based on Knock Sensor for Control Purpose Using Dedicated Signal Processing Platform

2008 ◽  
Author(s):  
Fabrice Guillemin ◽  
Olivier Grondin ◽  
Jonathan Chauvin ◽  
Emmanuel Nguyen
Keyword(s):  
Signal Processing ◽  
Parameters Estimation ◽  
Knock Sensor ◽  
Processing Platform ◽  
Control Purpose

Design of On-orbit Software Reconfiguration for a General Signal Processing Platform Based on SOC Chip

2021 ◽  
Author(s):  
Shengming Liang ◽  
Kang Wang ◽  
Haiyuan Wang ◽  
Ruichen Wang ◽  
Rui Guo
Keyword(s):  
Signal Processing ◽  
Software Reconfiguration ◽  
Processing Platform

scholarly journals Reducing of noise structure influence on an accuracy of a desired signal extraction

2018 ◽  
Vol 15 (3) ◽  
pp. 365-370 ◽  
Author(s):  
Vladimir Marchuk
Keyword(s):  
Signal Processing ◽  
Mathematical Expectation ◽  
Random Processes ◽  
Parameters Estimation ◽  
Signal Extraction ◽  
Scientific Contribution ◽  
Noise Component ◽  
Component Structure ◽  
Noise Structure ◽  
Theoretical Results

In the paper, the issues regarding the analysis of the noise component structure are addressed and methods for reducing the error in estimating of the mathematical expectation of the noise component are proposed. The use of the proposed method of ?noise purification? makes possibility to reduce the error introduced by the noise structure when estimating the mathematical expectation and dispersion of the noise component during research. The main scientific contribution in this paper in accuracy increasing of random processes parameters estimation. These theoretical results can be applied in different spheres of data analyzing and signal processing when random processes have some structure.

Parallel Programming and Its Architectures Based on Data Access Separated Algorithm Kernels

2012 ◽  
pp. 278-296
Author(s):  
Dake Liu ◽  
Joar Sohl ◽  
Jian Wang
Keyword(s):  
Signal Processing ◽  
Parallel Programming ◽  
High Performance ◽  
Data Access ◽  
Time Signal ◽  
Hardware System ◽  
Memory Subsystem ◽  
Computing Performance ◽  
Processing Platform ◽  
Parallel Signal Processing

A novel master-multi-SIMD architecture and its kernel (template) based parallel programming flow is introduced as a parallel signal processing platform. The name of the platform is ePUMA (embedded Parallel DSP processor architecture with Unique Memory Access). The essential technology is to separate data accessing kernels from arithmetic computing kernels so that the run-time cost of data access can be minimized by running it in parallel with algorithm computing. The SIMD memory subsystem architecture based on the proposed flow dramatically improves the total computing performance. The hardware system and programming flow introduced in this article will primarily aim at low-power high-performance embedded parallel computing with low silicon cost for communications and similar real-time signal processing.

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