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FIR
1、验证窗函数 N 变化时,验证其频谱主瓣副瓣比、主瓣宽度的变化。
a)矩形窗函数的 N 变化时,验证其其频谱主瓣副瓣幅度比基本不会发生变化,
而主瓣宽度将会变窄。这说明,当用矩形窗函数设计滤波器时,增大 N 不能使
得阻带衰减减小,但能够减小过渡带。
b)再选取其他的窗如 hamming/hanning 窗,验证当 N 变化时,其频谱主瓣宽
度变化、主瓣副瓣比值变化情况。
2、用窗函数法设计线性相位 FIR 低通,通带截止频率 wp=0.5PI, 阻带截止频率 ws=0.6PI,
阻带衰减不小于 40dB,通带衰减不大于 3dB.
a)选取 Hanning,Hamming 窗查看设计出来的 FIR 的过渡带宽和阻带衰减是否
满足要求,二者有什么不同。
b)使用 hamming 窗,将窗长增大 1 倍,设计 FIR。验证同样的窗函数类型
(hamming),不同窗长度时,设计出来的 FIR 的过渡带宽和阻带衰减都有什么变
化。
3、不使用 Matlab 系统函数得到上一项指标的低通,并与上一项结果比较。
4 用窗函数法设计线性相位 FIR 高通,通带截止频率 wp=0.8PI, 阻带截止频率
ws=0.7PI, 阻带衰减不小于 30dB,通带衰减不大于 3dB.(An actual filter is implemented using the truncated unit impulse response sequence of the ideal filter.
For the ideal low pass filter, the unit impulse response h, N, D () is intercepted by a length of N, and the length is
The N sequence H (n), when intercepted, guarantees causality and linear phase requirements for the filter.
In order to reduce the Gibbs effect, the H (n) window is added, and the appropriate window function is selected to ensure the stopband attenuation and
Transition zone requirement. Note that the sidelobe of the window function affects the stopband attenuation of the filter, and the main lobe width affects the filter
Transition bandwidth.)
- 2017-07-06 11:55:24下载
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二叉树自适应扫描顺序编码的matlab
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Continuous-system-discretization
连续系统离散化,欧拉梯形公式、三阶龙格-库塔法、汉明积分法、状态转移法(Continuous system discretization Euler trapezoid formula, the third-order Runge- Kutta method, Hamming integration method, the state transition method)
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最 短 路 dijkstra 算 法 mex 程 序,图论中的最短路径!
最 短 路 dijkstra 算 法 mex 程 序,图论中的最短路径!-Dijkstra shortest path algorithm mex procedures, graph theory of the shortest path!
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bianjieyue
说明: 变阶跃式PID控制matlab程序,同大家一同学习。(Variable step-type PID control matlab procedures, with everyone learning together.)
- 2008-10-11 09:43:41下载
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DimReduc
维数约简工具箱源代码,包括PCA、LLE等学习算法,可用于模式识别、数据挖掘和统计分析等。(dimension reduction toolkit source code, including the PCA, LLE and other learning algorithms can be used for pattern recognition, data mining and statistical analysis.)
- 2007-06-20 16:07:54下载
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pso-bp
粒子群算法,也称粒子群优化算法(Particle Swarm Optimization),缩写为 PSO, 是近年来发展起来的一种新的进化算法(Evolutionary Algorithm - EA)。PSO 算法属于进化算法的一种,和模拟退火算法相似,它也是从随机解出发,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。粒子群算法是一种并行算法。
BP(Back Propagation)神经网络是1986年由Rumelhart和McCelland为首的科学家小组提出,是一种按误差逆传播算法训练的多层前馈网络,是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系,而无需事前揭示描述这种映射关系的数学方程。它的学习规则是使用最速下降法,通过反向传播来不断调整网络的权值和阈值,使网络的误差平方和最小。BP神经网络模型拓扑结构包括输入层(input)、隐层(hidden layer)和输出层(output layer)。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years (Evolutionary Algorithm- EA). Kind, and simulated annealing algorithm PSO algorithm is similar evolutionary algorithms, it is also starting a random solution, through an iterative search for the optimal solution, which is also used to uate the quality through fitness solution, but it is simpler than genetic algorithm rules It has no genetic algorithm " crossover" (Crossover) and " variant" (Mutation) operation, which by following the current search to find the optimal value to the global optimum. This algorithm is its easy implementation, high accuracy, fast convergence, etc. attracted academic attention and show its superiority in solving practical problems. PSO algorithm is a parallel algorithm. BP (Back Propagation) neural network is a 1986 team of scientists headed by Rumelhart and McC)
- 2020-10-29 22:19:56下载
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PSOGSA
程序提出了一种基于人群混合算法,是粒子群优化和引力搜索算法的组合。主要目标提高整合PSO和GSA算法的能力(Hybrid Particle Swarm Optimization and Gravitational Search Algorithm (PSOGSA)
A new hybrid population-based algorithm (PSOGSA) is proposed with the combination of Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA). The main idea is to integrate the ability of exploitation in PSO with the ability of exploration in GSA to synthesize both algorithms’ strength. Some benchmark test functions are used to compare the hybrid algorithm with both the standard PSO and GSA algorithms in evolving best solution.)
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再玩一次
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亲测可用的粒子群算法(PSO)解决旅行商问题(TSP)matlab例程
采用热核构造权重,仿真效果非常好,含噪脉冲信号进行相关检测,matlab编写的元胞自动机,利用自然梯度算法,实现了对10个数字音的识别。
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