원문정보
초록
영어
According to the present medical monitoring system still exist the problems such as low accuracy of the condition judgment and the less range of data transmission, a kind of lung sounds signal separation model of medical monitoring is put forward based on wireless sensor network. First, using the optimization strategy of the flying speed and the effect between particles to two-way optimization for particle swarm optimization algorithm (PSOA), and then applied it to the blind source separation of lung sounds signal, in order to improve the precision of the blind source separation of lung sound signals, then carried on the optimization of artificial fish behavior through tabu search, did coverage optimization for wireless sensor network by using the improved algorithm, to expand the scope of wireless data transmission. As the simulation experiments results showed that, the proposed lung sounds signal separation model of medical monitoring based on wireless sensor network had good accuracy and large range of data transmission, and deserved to be popularized and used.
목차
1. Introduction
2. Lung Signal Separation Based on Improved Algorithm of Blind Source Separation
2.1. Mathematical Model of Blind Signal Separation
2.2. Blind Signals Separation Based on Improved PSO
3. The Coverage Optimization of Medical Monitoring Model Based on Wireless Sensor Network
3.1. The Behavior Description of the Artificial Fish Swarm Algorithm (SFSA)
3.2. Optimize the Coverage of Wireless Sensor Network Based on Improved Artificial Fish Swarm
4. The Performance Simulating of Algorithm
5. Conclusions
References