以1秒的滑动窗口生成重叠度为80%的chirp信号的python代码
时间: 2023-12-01 10:04:58 浏览: 26
以下是以1秒的滑动窗口生成重叠度为80%的chirp信号的Python代码示例:
```python
import numpy as np
import matplotlib.pyplot as plt
# 设置chirp信号的参数
fs = 44100 # 采样频率
T = 10 # 信号总时长
f0 = 100 # 起始频率
f1 = 1000 # 终止频率
t = np.linspace(0, T, int(fs*T)) # 时间轴
k = (f1-f0)/T # 调频率
# 生成初始的chirp信号
x = np.sin(2*np.pi*(f0*t + 0.5*k*t**2))
# 以1秒的时间间隔滑动窗口生成新的chirp信号
window_size = fs # 窗口大小为1秒
overlap_size = int(window_size*0.8) # 重叠大小为0.8秒
hop_size = window_size - overlap_size # 步长为0.2秒
num_windows = int(np.ceil(float(len(x))/hop_size))
chirp_signals = np.zeros((num_windows, window_size))
for i in range(num_windows):
start = i*hop_size
end = start + window_size
if end > len(x):
end = len(x)
chirp_signals[i,:end-start] = x[start:end]
# 对于每个新的chirp信号,与前一个窗口内的信号进行重叠
for i in range(1, num_windows):
previous_signal = chirp_signals[i-1, overlap_size:]
current_signal = chirp_signals[i, :window_size-overlap_size]
overlap = previous_signal[-overlap_size:] + current_signal[:overlap_size]
weight = np.linspace(0, 1, overlap_size)
chirp_signals[i,:overlap_size] = weight*overlap + (1-weight)*previous_signal[-overlap_size:]
chirp_signals[i,:window_size-overlap_size] += current_signal[overlap_size:]
# 将每个窗口内的信号数组相加,得到完整的重叠度为80%的chirp信号
chirp_signal = np.concatenate(chirp_signals)
# 绘制chirp信号的图像
plt.plot(t, chirp_signal)
plt.xlabel('Time (s)')
plt.ylabel('Amplitude')
plt.show()
```
需要注意的是,由于窗口滑动时需要进行大量的计算,因此在处理长时间的信号时可能需要一定的时间。为了加快处理速度,可以考虑使用并行计算等技术。