Abstract. An evolvable hardware (EHW) system for high-speed sonar return classification has been proposed. The system demonstrates an average accuracy of 91.4 % on a sonar spectrum data set. This is better than a feed-forward neural network and previously proposed EHW architectures. Furthermore, this system is designed for online evolution. Incremental evolution, data buses and high level modules have been utilized in order to make the evolution of the 480 bit-input classifier feasible. The classification has been implemented for a Xilinx XC2VP30 FPGA with a resource utilization of 81 % and a classification time of 0.5µs. 1

To improve traffic safety, an automatic traffic sign detection system would be important to assist the driver. In this paper, an approach for detecting Norwegian speed limit signs is proposed. It consists of three major steps: Color-based filtering, locating sign(s) in an image and detection of numbers on the sign. About 91 % correct recognition is achieved for a selection of 198 images. Ongoing work is focused on video input analysis.

An automatic sign detection system could be important in enhancing traffic safety. Such a system would have to be able to provide high speed processing in its real-time environment. In this paper, we show how one of the time consuming parts of a speed limit detection algorithm can be implemented in reconfigurable logic to speed up the processing. Results indicate that the present system would be able to handle 12 images per second. 1

Abstract—Evolvable Hardware (EHW) has been regarded as adaptive system acquired by wide application market. Consumer market of any good requires diversity to satisfy consumers’ preferences. Adaptation of EHW is a key technology that could provide individual approach to every particular user. This situation raises a question: how to set target for evolutionary algorithm? The existing techniques do not allow consumer to influence evolutionary process. Only designer at the moment is capable to influence the evolution. The proposed consumer-triggered evolution overcomes this problem by introducing new features to EHW that help adaptive system to obtain targets during consumer stage. Classification of EHW is given according to responsiveness, imitation of human behavior and target circuit response. Home intelligent water heating system is considered as an example. Keywords—Actuators, consumer-triggered evolution, evolvable hardware, sensors. I.