介绍了一种基于现场可编程门阵列(Field Programmable Gate Array,FPGA)和数字模拟转换器(Digital Analog Converter,DAC)的线性扫频信号发生器,在调研常用窄带频率信号发生器的基础上结合各方案的优缺点提出了一种FPGA内嵌式线性扫频...介绍了一种基于现场可编程门阵列(Field Programmable Gate Array,FPGA)和数字模拟转换器(Digital Analog Converter,DAC)的线性扫频信号发生器,在调研常用窄带频率信号发生器的基础上结合各方案的优缺点提出了一种FPGA内嵌式线性扫频信号发生器,系统用Verilog编程实现直接数字频率合成器(Direct Digital Synthesizer,DDS)并以此为基础实现扫频信号输出。软件系统给定起始扫频频率,截止扫频频率,频率跳变时间间隔,频率跳变大小四个参数,系统即按照设定的参数输出需要的扫频信号。文中给出了详细的设计原理,并给出了实验测试结果。展开更多
This paper highlights the memristor bridge-based lowpass filter (LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invar...This paper highlights the memristor bridge-based lowpass filter (LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invariant feature transform (SIFT). First, a novel kind of LPF based on the memristor bridge is designed, whose cut-off frequency and other traits are demonstrated to change with different time and memristance. In light of the changeable parameter of the memristor bridge-based LPF, a new adaptive Gaussian filter and an improved SIFT algorithm are presented. Finally, experiment results show that the peak signalto- noise ratio (PSNR) of our denoising is bettered more than 2.77 dB compared to the corresponding of the traditional Gaussian filter, and our improved SIFT performances including the number of matched feature points and the percent of correct matches are higher than the traditional SIFT, which verifies feasibility and effectiveness of our algorithm.展开更多
文摘介绍了一种基于现场可编程门阵列(Field Programmable Gate Array,FPGA)和数字模拟转换器(Digital Analog Converter,DAC)的线性扫频信号发生器,在调研常用窄带频率信号发生器的基础上结合各方案的优缺点提出了一种FPGA内嵌式线性扫频信号发生器,系统用Verilog编程实现直接数字频率合成器(Direct Digital Synthesizer,DDS)并以此为基础实现扫频信号输出。软件系统给定起始扫频频率,截止扫频频率,频率跳变时间间隔,频率跳变大小四个参数,系统即按照设定的参数输出需要的扫频信号。文中给出了详细的设计原理,并给出了实验测试结果。
基金supported by the National Natural Science Foundation of China(61550110248)
文摘This paper highlights the memristor bridge-based lowpass filter (LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invariant feature transform (SIFT). First, a novel kind of LPF based on the memristor bridge is designed, whose cut-off frequency and other traits are demonstrated to change with different time and memristance. In light of the changeable parameter of the memristor bridge-based LPF, a new adaptive Gaussian filter and an improved SIFT algorithm are presented. Finally, experiment results show that the peak signalto- noise ratio (PSNR) of our denoising is bettered more than 2.77 dB compared to the corresponding of the traditional Gaussian filter, and our improved SIFT performances including the number of matched feature points and the percent of correct matches are higher than the traditional SIFT, which verifies feasibility and effectiveness of our algorithm.
