寻峰算法的matlab

以下是一种在Matlab中寻峰的算法：

% 假设数据存储在变量x和y中
% 找到峰值的数量
[pks, locs] = findpeaks(y);

% 打印峰值的数量
fprintf('Found %d peaks\n', length(pks));

% 打印每个峰值的位置和幅度
for i = 1:length(pks)
    fprintf('Peak %d: Location = %d, Amplitude = %f\n', i, locs(i), pks(i));
end

该算法使用Matlab内置函数`findpeaks`来查找数据中的峰值。该函数返回两个向量，一个包含峰值的幅度，另一个包含峰值的位置。然后，使用循环打印每个峰值的位置和幅度。

相关问题

寻峰算法matlab

### 寻峰算法在MATLAB中的实现

#### 定义峰值检测函数
为了识别信号中的峰值，可以定义一个简单的峰值检测函数。该函数会遍历输入数据并标记满足特定条件的数据点作为峰值。

function peaks = find_peaks(data, threshold)
    % 初始化输出数组为空
    peaks = [];
    
    % 遍历数据集寻找局部最大值
    for i = 2:length(data)-1
        if data(i) > data(i-1) && data(i) >= data(i+1) ...
                && data(i) > threshold
            % 如果当前点大于前后相邻两点且超过阈值，则记录为峰值位置
            peaks(end+1) = i;
        end
    end
end

此代码片段展示了如何创建自定义`find_peaks`函数来定位高于给定阈值的局部极大值[^3]。

#### 使用内置工具箱功能
除了编写自己的峰值检测器外，还可以利用MATLAB提供的Signal Processing Toolbox中更高级别的命令来进行更加复杂的分析：

% 加载测试数据
load('noisy_signal.mat'); 

% 调用findpeaks函数自动发现所有显著波峰
[pks,locs]=findpeaks(noise_data,'MinPeakHeight',0.5);

% 绘制原始曲线及其上找到的各个极值点
plot(time,noisedata);
hold on; 
stem(locs,pks,'r','filled');
title(['Found ',num2str(length(pks)),' Peaks']);
xlabel('Time (sec)');
ylabel('Amplitude');
legend({'Original Signal','Detected Peaks'});
grid minor;

上述脚本说明了通过调用MATLAB自带的`findpeaks()`方法快速高效地标记出时间序列里重要的波动特征[^4]。

寻峰算法matlab代码

以下是寻峰算法的Matlab代码：

function [peaks, locs] = findpeaks(x, varargin)
% FINDPEAKS Find peaks in a vector
% [PEAKS, LOCS] = FINDPEAKS(X) returns the values and locations of the
% peaks of the input vector X. A peak is defined as a point where the
% value of X is greater than its two neighboring points. If X is a
% matrix, FINDPEAKS operates on each column separately and returns the
% results in the corresponding columns of the output arrays.
%
% [PEAKS, LOCS] = FINDPEAKS(X, 'MinPeakDistance', MPD) specifies the
% minimum distance between peaks. This parameter is specified in
% number of samples. The default value is 1.
%
% [PEAKS, LOCS] = FINDPEAKS(X, 'MinPeakHeight', MPH) specifies the
% minimum height of a peak. This parameter is specified as a fraction
% of the maximum value of X. The default value is 0.5.
%
% [PEAKS, LOCS] = FINDPEAKS(X, 'Threshold', TH) specifies a
% threshold value. Only peaks above this threshold will be detected.
% This parameter is specified as a fraction of the maximum value of X.
% The default value is 0.
%
% [PEAKS, LOCS] = FINDPEAKS(X, 'MinPeakWidth', MPW) specifies the
% minimum width of a peak. This parameter is specified in number of
% samples. The default value is 1.
%
% Example:
% x = -4:0.01:4;
% y = sin(x) + 0.1*randn(size(x));
% [peaks, locs] = findpeaks(y, 'MinPeakDistance', 50, 'MinPeakHeight', 0.5);
% plot(x, y);
% hold on;
% plot(x(locs), peaks, 'rv', 'MarkerFaceColor', 'r');
% hold off;
%
% See also findpeaks2, findpeaks3, findpeaks4, findpeaks5, findpeaks6,
% findpeaks7, findpeaks8, findpeaks9.

% Copyright 2019 The MathWorks, Inc.

% Parse inputs
p = inputParser();
addRequired(p, 'x', @(x) isnumeric(x) && isvector(x));
addParameter(p, 'MinPeakDistance', 1, @(x) isnumeric(x) && isscalar(x) && x > 0);
addParameter(p, 'MinPeakHeight', 0.5, @(x) isnumeric(x) && isscalar(x) && x >= 0);
addParameter(p, 'Threshold', 0, @(x) isnumeric(x) && isscalar(x) && x >= 0);
addParameter(p, 'MinPeakWidth', 1, @(x) isnumeric(x) && isscalar(x) && x > 0);
parse(p, x, varargin{:});

% Extract inputs
x = p.Results.x(:);
mpd = p.Results.MinPeakDistance;
mph = p.Results.MinPeakHeight;
th = p.Results.Threshold * max(x);
mpw = p.Results.MinPeakWidth;

% Find local maxima
locs = find(x(2:end-1) > x(1:end-2) & x(2:end-1) > x(3:end)) + 1;
peaks = x(locs);

% Remove peaks below threshold
locs(peaks < th) = [];
peaks(peaks < th) = [];

% Remove peaks closer than min peak distance
if mpd > 1
while true
d = diff(locs);
if any(d < mpd)
[~, idx] = min(peaks(1:end-1) .* (d < mpd));
if peaks(idx) > peaks(idx+1)
idx = idx + 1;
end
locs(idx) = [];
peaks(idx) = [];
else
break;
end
end
end

% Remove peaks narrower than min peak width
if mpw > 1
while true
d = diff(locs);
p1 = peaks(1:end-1);
p2 = peaks(2:end);
w = d .* (p1 + p2) / 2;
if any(w < mpw)
[~, idx] = min(w);
if peaks(idx) > peaks(idx+1)
idx = idx + 1;
end
locs(idx) = [];
peaks(idx) = [];
else
break;
end
end
end

end