ฝัง
- เผยแพร่เมื่อ 10 ก.ย. 2024
- Adding Noise to a Sine Wave and Normalizing the Result
In this video, we explore the process of generating a sine wave and adding noise to it using Python. We then normalize the resulting mixed signal and visualize a portion of it.
Code Breakdown:
Generate Sine Wave and Noise Tone:
We generate a 500 Hz sine wave.
We generate a 25,000 Hz noise tone and scale it down by multiplying it by 0.3 to reduce its amplitude.
Mix the Tones:
We combine the sine wave and the noise tone to create a mixed signal.
Normalization:
We normalize the mixed signal to ensure the values fit within the range of 16-bit integers.
Visualization:
We plot the first 1,000 samples of the normalized mixed signal to visualize the impact of the added noise.
code
import numpy as np
import matplotlib.pyplot as plt
Function to generate a sine wave
def generate_sine_wave(freq, sample_rate, duration):
x = np.linspace(0, duration, sample_rate * duration, endpoint=False)
frequencies = x * freq
y = np.sin((2 * np.pi) * frequencies)
return x, y
Define the sample rate (samples per second) and duration (seconds)
SR = 60000 # Sample rate in Hertz (Hz)
T = 4 # Duration in seconds
Generate sine wave and noise tone
_, signal_tone = generate_sine_wave(500, SR, T) # generate a 500 Hz sine wave
_, noise_tone = generate_sine_wave(25000, SR, T) # generate a 25000 Hz noise tone
noise_tone = noise_tone * 0.3
Mix the tones
mixed_tone = signal_tone + noise_tone
Normalization of the results
normalized_tone = np.int16((mixed_tone / mixed_tone.max()) * 32767)
Plot the normalized mixed tone
plt.plot(normalized_tone[:1000])
plt.xlabel('Sample Number')
plt.ylabel('Amplitude')
plt.title('Normalized Mixed Signal (First 1000 Samples)')
plt.show()
