Explore MATLAB source code curated for "逆变换" with clean implementations, documentation, and examples.
(1) A MATLAB-based implementation example of Fourier transform and inverse transform, thoroughly tested and verified. (2) C++ source code for Fourier and inverse Fourier transform algorithms, successfully validated.
Curvelet Transform 1 implementation for performing curvelet decomposition to obtain coefficient matrices, including inverse transform functionality
This MATLAB implementation covers QPSK modulation and demodulation, including serial-to-parallel conversion, Fourier transforms and inverse transforms, channel estimation using Least Squares (LS) criterion, and Doppler shift compensation modules with clear code demonstrations and algorithm explanations.
Image descriptions: A: Spectrum after Fourier transform; B: Spectrum after notch filter application; C: Filtered image after inverse transform (results not optimal). Ifft2: To validate the custom FFT program's correctness, used MATLAB's built-in ifft2 function for inverse transformation - output matches original image, confirming proper FFT implementation.
MATLAB-implemented FFT and IFFT functions written in M-language with executable code, supporting spectral analysis and signal processing applications.
Performing Fast Fourier Transform on images, removing high-frequency information in the frequency domain, and applying inverse transform to spatial domain to eliminate image raster artifacts with implementation insights.
Speech signal denoising implementation in MATLAB environment, performing wavelet transform on noisy speech signals, applying threshold-based denoising principles, and reconstructing enhanced speech signals through inverse transformation with detailed algorithm explanation.
1. Select an image and perform DCT block operations (dividing image into 8×8 blocks, applying DCT transform to each block). 2. Use masking matrix for DCT coefficient region selection, perform inverse DCT to reconstruct original image, and calculate PSNR of synthesized image. 3. Choose a wavelet function to decompose an image, display transform coefficients to observe patterns, and perform inverse wavelet transform for image reconstruction.
MATLAB-based image enhancement implementation using Haar wavelet transform, featuring forward/inverse wavelet transforms with decomposition and reconstruction source code. The algorithm processes image data through multi-level wavelet decomposition, applies enhancement techniques to wavelet coefficients, and reconstructs the enhanced image.
Research on time-frequency characteristics of time series including Fourier transform and inverse transform, fast Mellin transform and inverse transform, short-time discrete Fourier transform for instantaneous frequency extraction. Implementation of time-frequency distributions: Born-Jordan distribution, Butterworth distribution, and Choi-Williams distribution for visualizing instantaneous frequency patterns.