A hybrid approach for acoustic signal segmentation by computing similarity matrix, novelty score and peak detection for vehicular classification in wireless sensor networks

INTERACT-2010 ◽  
2010 ◽  
Author(s):  
G. Padmavathi ◽  
D. Shanmugapriya ◽  
M. Kalaivani
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Acoustic Signal ◽  
Hybrid Approach ◽  
Peak Detection ◽  
Wireless Sensor ◽  
Similarity Matrix ◽  
Signal Segmentation

scholarly journals A Novel Hybrid Approach for Optimizing the Localization of Wireless Sensor Networks

2018 ◽  
Vol 200 ◽  
pp. 00005
Author(s):  
Halima Lakhbab
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Global Positioning System ◽  
Physical Environment ◽  
Optimization Problem ◽  
Hybrid Approach ◽  
Wireless Sensor ◽  
Swarm Optimization ◽  
Unconstrained Optimization Problem ◽  
Global Positioning

Wireless sensor networks are used for monitoring the environment and controlling the physical environment. Information gathered by the sensors is only useful if the positions of the sensors are known. One of the solutions for this problem is Global Positioning System (GPS). However, this approach is prohibitively costly; both in terms of hardware and power requirements. Localization is defined as finding the physical coordinates of a group of nodes. Localization is classified as an unconstrained optimization problem. In this work, we propose a new algorithm to tackle the problem of localization; the algorithm is based on a hybridization of Particle Swarm Optimization (PSO) and Simulated Annealing (SA). Simulation results are given to illustrate the robustness and efficiency of the presented algorithm.

Sign in / Sign up

Export Citation Format

Share Document