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The paper introduces new implementation methods of the fuzzy interpreted Petri net (FIPN) on FPGAs. The realization of FIPN is based on fast array multipliers and multipliers utilizing DSP blocks available on FPGA systems. The paper contains descriptions of particular network components' architectures and results of simulations of these components. In the paper a real control system is designed, which is used to show properties of FIPN. A few slightly different implementations of the example control system as well as their comparison in terms of FPGA resources requirement and calculations speed are also featured. The conducted experiments revealed that the proposed FPGA implementation is many times faster than software realizations of the same control system exercising typical microprocessors and microcontrollers. INDEX TERMS Fuzzy interpreted Petri net, intelligent control systems modeling and analysis, FPGA implementation.

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Trained sonar operators participated in a detection and classification task. Stimuli were presented in three conditions: auditory and visual modalities independently and simultaneously (multimodal). The signal-to-noise ratio (SIN) was continually increased during a trial, and the elapsed time as well as the SIN level at detection and classification were recorded. The best modality for target detection was found to be target specific. However, the multimodal condition was not significantly different from the single best modality and, therefore, should be used for initial target detection in the operational setting. Differences from findings in previous studies are discussed.

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