BVAR_Analytical

说明：  关于脉冲压缩的问题。脉冲压缩的质量直接影响雷达的探测性能。(Pulse compression on the issue. Direct impact on the quality of pulse compression radar detection performance.)

利用黄金分割法来求解目标函数的局部极小值。(Functions using golden section method for the minimum.)

基于EKF的SOC估算建模仿真论文期刊文章(EKF SOC estimates the journal articles based on Modeling and simulation )

synthic aperture radar ieee papers

this is speech recognition file

这个主要是人脸识别的分块显示程序，是三阶临进的(This is the main face recognition sub-block display program, and third-order Pro into)

多极点控制算法的实际应用案例，适合振动控制系统(Multipolar point control algorithm is practical application cases, suitable for vibration control system)

NSString框架的学习，包括NSNumber等 NSString框架的学习，包括NSNumber等(NSString framework of learning, including learning NSNumber etc. NSString framework, including NSNumber etc.)

LTE (Long Term Evolution) and LTE-Advanced have been developed to respond to the requirements of this era and to realize the goal of achieving global broadband mobile communications. The goals and objectives of this evolved system include higher radio access data rates, improved system capacity and coverage, flexible bandwidth operations, significantly improved spectral efficiency, low latency, reduced operating costs, multi-antenna support, and seamless integration with the Internet and existing mobile communication systems. The LTE physical layer includes transmissions in uplink and downlink. The uplink transmissions are governed by PUSCH. The throughput performance of PUSCH is analyzed here

线性递减权重粒子群优化算法是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。 (Linear decreasing weight particle swarm optimization starting from random solutions to find the optimal solution by iteration, it is also the fitness to evaluate the quality of the solution, but it is much simpler than the genetic algorithm rules, it is not a genetic algorithm " cross" (Crossover) and " variation" (Mutation) operation, which follow the current search for the optimal value to find the global optimum. The advantage of this algorithm is its ease of implementation, high accuracy, fast convergence and attracted the attention of the academic community, and demonstrated its superiority in solving practical problems.)