Qo'llash sohalari:
6. Signalni o'chirish:
Haar to'lqinli o'zgarishlar signalni shovqindan ajratish uchun ishlatiladi. Yuqori chastotali tafsilot koeffitsientlari ko'pincha shovqinni ifodalaydi, bu muhim signal xususiyatlarini saqlab qolgan holda uni olib tashlash imkonini beradi.
7. Rasmni siqish:
Tasvirni qayta ishlashda siqishni uchun Haar to'lqinli o'zgarishlar qo'llaniladi. Haar domenidagi tasvirlarni ifodalash orqali tasvir sifatini minimal yo'qotgan holda samarali siqilishga erishish mumkin.
8. Ma'lumotlarni tahlil qilish:
Haar to'lqinli o'zgarishlar ma'lumotlarni tahlil qilishda ilovalarni topadi, ayniqsa signallar yuqori va past chastotali komponentlarni ko'rsatadigan hollarda.
1 – topshiriq
Dastur kodi:
import numpy as np
import matplotlib.pyplot as plt
import pywt
def function(x):
return (x**2 - 1) * np.exp(3*x + 1)
x_values = np.arange(-3,4,0.02)
z_values=function(x_values)
# print(z_values)
coeffs = pywt.wavedec(z_values, 'haar')
coeffs[5:] = [np.zeros_like(v) for v in coeffs[5:]]
hara_signal = pywt.waverec(coeffs, 'haar')
plt.figure(figsize=(10, 6))
plt.plot(x_values,z_values,label='Asl Signal')
plt.plot(x_values, hara_signal, label='Hara wavelet Signal', line)
plt.legend()
plt.title("Asl va Hara wavelet bilan o'zgartirilgan signal")
plt.xlabel('x')
plt.ylabel('y')
plt.show()
Dastur natijalari:
1 – rasm. Funkisyaga hara wavelet o’zgartirishini qo’llash
2 – rasm. Funkisyaga hara wavelet o’zgartirishi kiritlgandagi natija
.
2 - topshiriq
Datsur kodi:
import numpy as np
import pywt
from scipy.io import wavfile
import matplotlib.pyplot as plt
def haar_wavelet_transform(audio_data):
coeffs = pywt.wavedec(audio_data, 'haar')
return coeffs
def inverse_haar_wavelet_transform(coeffs):
reconstructed_audio = pywt.waverec(coeffs, 'haar')
return reconstructed_audio
file_path = '/content/diyor.wav'
sample_rate, audio_data = wavfile.read(file_path)
coeffs = haar_wavelet_transform(audio_data)
coeffs[6:] = [np.zeros_like(v) for v in coeffs[6:]]
reconstructed_audio = inverse_haar_wavelet_transform(coeffs)
plt.figure(figsize=(10, 6))
plt.subplot(2, 1, 1)
plt.plot(audio_data, label='Asl audio')
plt.legend()
plt.title('Asl audio signal')
plt.xlabel('Indekslar')
plt.ylabel('Amplituda')
plt.subplot(2, 1, 2)
plt.plot(reconstructed_audio, label='Hara walevet Audio', line)
plt.legend()
plt.title('Hara audio Signal')
plt.xlabel('Indekslar')
plt.ylabel('Amplituda')
plt.tight_layout()
plt.show()
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