摘要：【中文】本发明公开了一种具有滤波功能的差分移相器，包括：介质基板、金属地层和微带结构，金属地层和微带结构设置在介质基板上，所述微带结构包括相互独立的第一二端口网络和第二二端口网络，所述第一二端口网络和所述第二二端口网络结构均包括时延线、耦合线和传输线网络，所述传输线网络与所述时延线、所述耦合线连接，其中所述耦合线的电长度为中心频率对应波长的四分之一，所述传输线网络包括第一传输线，所述第一传输线的电长度为中心频率对应波长的四分之三。本发明使得信号通过时，耦合线和第一传输线的电长度相差180度，信号产生相干相消，在中心频点处保留通带，在带宽外产生阻带，实现滤波功能，可广泛应用于移相器领域。 【EN】The invention discloses a differential phase shifter with a filtering function, which comprises: the microstrip structure comprises a first two-port network and a second two-port network which are independent of each other, the first two-port network and the second two-port network respectively comprise a delay line, a coupling line and a transmission line network, the transmission line network is connected with the delay line and the coupling line, the electrical length of the coupling line is one fourth of the wavelength corresponding to the center frequency, the transmission line network comprises a first transmission line, and the electrical length of the first transmission line is three quarters of the wavelength corresponding to the center frequency. When the signal passes through the phase shifter, the difference between the electrical lengths of the coupling line and the first transmission line is 180 degrees, the signal is subjected to coherence cancellation, a passband is reserved at a central frequency point, a stop band is generated outside the bandwidth, the filtering function is realized, and the phase shifter can be widely applied to the field of phase shifters.

摘要：【中文】本发明公开了基于差分进化算法的局部搜索和全局搜索融合方法及系统，方法包括：对种群参数进行初始化配置，生成初始种群；配置局部搜索代数计数器和全局搜索代数计数器；在种群进入局部搜索阶段时，确定局部搜索代数计数器处于上限和下限之间且子种群没有收敛后，种群进入全局搜索阶段；判断全局搜索代数计数器的值是否小于全局搜索代数的上限，若是，则重新执行全局搜索阶段；反之，则返回执行配置局部搜索代数计数器和全局搜索代数计数器的步骤，直至确定达到初始化配置的差分进化算法执行的终止条件后，结束所述差分进化算法。本发明增强了种群的收敛性和探索性，提高了搜索的全面性，高效且复杂度低，可广泛应用于数值优化技术领域。 【EN】The invention discloses a local search and global search fusion method and a system based on a differential evolution algorithm, wherein the method comprises the following steps: carrying out initialization configuration on population parameters to generate an initial population; configuring a local search algebra counter and a global search algebra counter; when the population enters a local search stage, determining that a local search algebraic counter is between an upper limit and a lower limit and a sub-population is not converged, and then entering a global search stage; judging whether the value of the global search algebra counter is smaller than the upper limit of the global search algebra, if so, re-executing the global search stage; otherwise, returning to the step of executing and configuring the local search algebra counter and the global search algebra counter until the termination condition of the execution of the initially configured differential evolution algorithm is determined, and ending the differential evolution algorithm. The invention enhances the convergence and searchability of the population, improves the comprehensiveness of the search, has high efficiency and low complexity, and can be widely applied to the technical field of numerical optimization.