Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Embedded Software-Based Self-Test for Programmable Core-Based Designs
IEEE Design & Test
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Applying the Oscillation Test Strategy to FPAA's Configurable Analog Blocks
Journal of Electronic Testing: Theory and Applications
Testing the Interconnect Networks and I/O Resources of Field Programmable Analog Arrays
VTS '05 Proceedings of the 23rd IEEE Symposium on VLSI Test
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Energy Efficient Software-Based Self-Test for Wireless Sensor Network Nodes
VTS '06 Proceedings of the 24th IEEE VLSI Test Symposium
Distributed fault detection of wireless sensor networks
DIWANS '06 Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks
Addressing the Metric Challenge: Evolved versus Traditional Fault Tolerant Circuits
AHS '07 Proceedings of the Second NASA/ESA Conference on Adaptive Hardware and Systems
Built-In Self-Test of Field Programmable Analog Arrays based on Transient Response Analysis
Journal of Electronic Testing: Theory and Applications
Multiobjective Optimization: Interactive and Evolutionary Approaches
Multiobjective Optimization: Interactive and Evolutionary Approaches
Wired and wireless sensor networks for industrial applications
Microelectronics Journal
Research on fault-tolerance of analog circuits based on evolvable hardware
ICES'07 Proceedings of the 7th international conference on Evolvable systems: from biology to hardware
Microprocessor Software-Based Self-Testing
IEEE Design & Test
Based on PSoC Electric Angle Meter
RVSP '11 Proceedings of the 2011 First International Conference on Robot, Vision and Signal Processing
| Hi-index | 0.00 |
This paper presents an adaptive amplifier that is part of a sensor node in a wireless sensor network. The system presents a target gain that has to bemaintained without direct human intervention despite the presence of faults. In addition, its bandwidthmust be as large as possible. The system is composed of a software-based built-in self-test scheme implemented in the node that checks all the available gains in the amplifiers, a reconfigurable amplifier, and a genetic algorithm (GA) for reconfiguring the node resources that runs on a host computer. We adopt a PSoC device from Cypress for the node implementation. The performance evaluation of the scheme presented is made by adopting four different types of fault models in the amplifier gains. The fault simulation results show that GA finds the target gain with low error, maintains the bandwidth above theminimum tolerable bandwidth, and presents a runtime lower than exhaustive search method.