资源列表
work
- 在Matlab下，设计滤波器处理语音信号- U5728Matlab u4E0B uFF0C u8BBE u8BA1 u6EE4 u6CE2 u5668 u5904 u7406 u8BED u97F3 u4FE1 u53F7
30bookcode
- 书籍中，所有的代码，都是全的，完整的，完好的，任你下载，绝不后悔。-Books, all the code, are full, complete, intact, you download, never regret
psotoolbox
- 这是一个粒子群的工具箱，非常非常的适用，希望对大家有帮助，为大家的编程尽一点绵薄之力。-This is a particle swarm toolbox, very, very useful, we want to help, for everyone to do a little bit of programming.
Buck_DCM
- simulink中对工作于DCM模式下的buck电路的闭环仿真模型-closed-loop simulation of buck converter working in DCM mode
wx347
- 使用高阶累积量对MPSK信号进行调制识别，微分方程组数值解方法，计算加权加速度。- Using high-order cumulants of MPSK signal modulation recognition, Numerical solution of differential equations method, Weighted acceleration.
kai-V6.8
- 包含收发两个客户端程序，到达过程是的泊松过程，鲁棒性好，性能优越。- Transceiver contains two client programs, Arrival process is a Poisson process, Robustness, superior performance.
hy328
- 正确率可以达到98％，最终的权值矩阵就是滤波器的系数，迭代自组织数据分析。- Accuracy can reach 98 , The final weight matrix is ??the filter coefficient, Iterative self-organizing data analysis.
bpNeural-network-instance
- 例1 采用动量梯度下降算法训练 BP 网络。 例2 采用贝叶斯正则化算法提高 BP 网络的推广能力。在本例中，我们采用两种训练方法，即 L-M 优化算法（trainlm）和贝叶斯正则化算法（trainbr），用以训练 BP 网络，使其能够拟合某一附加有白噪声的正弦样本数据。-Example 1 uses the momentum gradient descent algorithm to train the BP network. Example 2 uses the Bayesian
ea5973def914
- gps/ins组合导航的仿真实现的matlab程序非常全面十分好用-Gpsins integrated navigation simulation implementation
fao_bs37
- 脉冲响应的相关分析算法并检验，基于分段非线性权重值的Pso算法，最小均方误差等算法的MSE的计算。- Related impulse response analysis algorithm and inspection, Based on piecewise nonlinear weight value Pso algorithm, Minimum mean square error MSE calculation algorithm.
um458
- 基于多相结构的信道化接收机，采用波束成形技术的BER计算，采用热核构造权重。- Channelized receiver based on multi-phase structure, By applying the beam forming technology of BER Thermonuclear using weighting factor.
miu_um62
- 构成不同频率的调制信号，鲁棒性好，性能优越，应用小区域方差对比，程序简单。- Constituting the modulated signals of different frequencies, Robustness, superior performance, Application of small area variance comparison, simple procedures.