Research On The Sliding DFT Algorithm

The standard method for spectrum analysis in digital signal processing is the discrete Fourier transform(DFT), typically implemented using a fast Fourier transform(FFT) algorithm. However , there are real-time applications that require spectrum analysis only over a subset of the N center frequencies of an N-point DFT,and require fewer computations. As a result, this dissertation studies an efficient algorithm - the sliding DFT algorithm whose spectral bin output rate is equal to the input data rate.The first part introduces the development of the discrete Fourier transform, and the importance in digital signal processing theory. the second part introduces the theory of the sliding DFT algorithm, including the calculate way principle, the structure realization, MATLAB simulation, the stability of the sliding DFT, the spectral leakage of the sliding DFT, Goertzel algorithm for a single DFT output. In the following part, the optimized algorithms of multiple-sample sliding DFT and adaptive sliding DFT are studied.. The fourth part extends some application of the sliding DFT, such as the application to the field of electrocardiogram signal analysis, a FM-noise squelch detector by sliding DFT algorithm, the application to the field of OFDM.The sliding DFT algorithm is a high-performance algorithm, In a real-time oriented system, the sliding DFT provides computational advantages over the traditional DFT oe FFT for many applications requiring successive output calculations, especially when only a subset of the DFT output bins are required.