Topic: radix-2 Goto Github
Some thing interesting about radix-2
Some thing interesting about radix-2
radix-2,A fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier transform of a sequence. Decomposing an N-point time domain signal into sequence of single points. The N-spectra are synthesized into a single frequency spectrum.
User: anandketan
radix-2,A comparison study between different FFT algorithms implemented in Java as part of the bachelor's degree. Implemented algorithms: Furier transform by definition, radix-2 (DIT) recursive, radix-2 (DIT) iterative, radix-2 (DIF) recursive, radix-4 (DIT) recursive, radix-4 (DIF) recursive, radix-4 (DIT) iterative, split radix (DIT), split radix (DIF), Bluestein's algoritm.
User: flinch010
radix-2,FFT - Radix2 DIT
User: hnkr
radix-2,Fully pipelined Integer Scaled / Unscaled Radix-2 Forward/Inverse Fast Fourier Transform (FFT) IP-core for newest Xilinx FPGAs (Source language - VHDL / Verilog). GNU GPL 3.0.
User: hukenovs
radix-2,A 32-point pipelined Fast Fourier transform processor, using single path delay architecture, and based on radix2-DIF(decimation-in-frequency) algorithm. The average SNR = 58.76.
User: jasonlin316
radix-2,Small library for in-place bit reversed DIT DFT radix-2 FFT using the same definition as MATLAB. Functions are provided for 1D and 2D FFTs as well as fftshift and fftshift2 which rearranges the components to place the 0 frequency term in the centre.
User: michael-md
radix-2,This is a repository where I added my DSP codes that have written in Matlab (without built-in function). I have also commented inside every code so that it will become helpful for newbies. Also added cross-check using Library Function.
User: saifergit
radix-2,Case studies constitute a modern interdisciplinary and valuable teaching practice which plays a critical and fundamental role in the development of new skills and the formation of new knowledge. This research studies the behavior and performance of two interdisciplinary and widely adopted scientific kernels, a Fast Fourier Transform and Matrix Multiplication. Both routines are implemented in the two current most popular many-core programming models CUDA and OpenACC. A Fast Fourier Transform (FFT) samples a signal over a period of time and divides it into its frequency components, computing the Discrete Fourier Transform (DFT) of a sequence. Unlike the traditional approach to computing a DFT, FFT algorithms reduce the complexity of the problem from O(n2) to O(nLog2n). Matrix multiplication is a cornerstone routine in Mathematics, Artificial Intelligence and Machine Learning. This research also shows that the nature of the problem plays a crucial role in determining what many-core model will provide the highest benefit in performance.
User: shadyboukhary
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