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In view of the digital geophone self-test system application demand for a variety of high quality waveform signal. This paper introduces a kind of design method of direct digital synthesis waveform signal generator based on FPGA. It mainly discusses the principle of the method of frequency synthesis technology, design thinking and implementation method. And using the design method of pipeline structure to improve circuit structure of 48 bits phase accumulator, so as to improve the running speed, and further increase the resolution of frequency synthesis. The test shows that the signal generator can produce sine wave, square wave, sawtooth wave, triangle wave. The frequency resolution can reach 0.18μHz. The highest output frequency is up to 20MHz, and frequency switch time is 20ns.

In this article, a design method of asynchronous FIFO memory based on FPGA is put forward. With FPGA as the core controller, We adopt Verilog HDL and top-down design method to build a top-level module design and also analyze the mark logic of asynchronous FIFO and the elimination of semi-stable state under Quartus II development platform. Besides, with the application of Gray code conversion technology, not only the reliable transmission of data is guaranteed but also design efficiency is improved. Through contrast experiment analysis and simulation test, the validity and reliability of asynchronous FIFO memory are verified, meeting the basic requirement that FIFO can hold more enough data without spillovers despite the fullness of data.

According to the requirements of general surgical operation, we designed the plasma therapy system which took the microprocessor as the control core based on medical low temperature plasma technology. Making use of High-frequency AC electric field exciting ions in the electrolyte can generate low temperature plasma. Conclusion: the low-temperature plasma therapy system can significantly reduce blood loss and length of incision, shorten operating time, and postoperative complications in general surgical operation.

Both maximum entropy method and Particle swarm optimization (PSO) are common threshold segmentation methods which have been used not only in image segmentation, but also in multi-threshold segmentation. Maximum entropy method is time-consuming, PSO may easily get trapped in a local optimum. In view of this concerning issue, we propose the PSO and maximum entropy are combined to make improvements on the PSO introduced in expansion model and opposition-based module. The objective functions of the maximum entropy as well as the PSO are obtained, which have improved to optimize them and search the optimal threshold combination, to achieve multi-threshold image segmentation. The results demonstrate that the new algorithm improved the segmentation speed and enhanced the robustness. And the optimizing results are stable.

In this article, a design of multi-channel data acquisition system is presented. With FPGA as the core controller, the system can implement logic control over the high-speed ADC and acquire high-speed and high-resolution sample data. Using asynchronous FIFO as a cache, it can transfer data between two different clock domains: ADC data acquisition module and RS485 data module, which helps to improve the work efficiency and data throughput of the system. In the Quartus II development platform, Verilog hardware description language is adopted and finite state machine so that parallel acquisition operation to multi-channel ADC controlled by FPGA can be achieved and the system can become equipped with high-resolution, strong real-timeliness, low noise interference and other advantages. When it comes to the final step, simulation of AD sampling, asynchronous FIFO and RS485 transmission are conducted under the Modelsim environment and on-line testing by Signaltap to the system is synchronously implemented. The validity and reliability of the system are verified.

To improve the accuracy and robustness of the moving object detection in the image sequence, the author improves the traditional algorithm which is based on the gray-value difference. The author makes good use of the color information of images and applies the pixels in red, green, blue the three component value as its identifying information. According to the background image color composition, it adapts and adjusts the proportion of the three groups. Dynamic threshold is used to do the binarization separation of the background difference image. The simulation experiment shows, this algorithm makes full use of the color features of image and achieve the expected goal of high recognizability and good robustness.