How does matlab filter a square wave into a sine wave through digital filtering, and the frequency o

Hello! In MATLAB, you can use FFT to carry out Fourier change on the signal, assuming that the time domain signal is A(N), then the process of Fourier transform is F(N)=FFT(A(N)), what you mean by fundamental wave, it should mean carrier, for example, we emit a small energy signal, we need a high-frequency carrier as a carrier, generally speaking, carriers are high-frequency signals, so use FDAtool in MATLAB to generate a low-pass filter, and the passband cut-off frequency should be less than the fundamental frequency, and then multiply the filter response in the frequency domain with the Fourier transform result, and then use IFFT to do the inverse Fourier transform of the obtained result.

In order to get a sine wave after square wave filtering, two conditions are required: 1. The 3rd harmonic (except for the fundamental and DC components) with a cut-off frequency lower than the lowest order of the square wave 2. In order to filter out the harmonics above the 3rd harmonic, the stop band of the low-pass filter must have a fast attenuation speed. You are using a second-order voltage-controlled voltage source low-pass filter with a stopband attenuation speed of -40dB 10 times.

A more reasonable cut-off frequency is to take the fundamental frequency or a slightly higher frequency to minimize the attenuation of more than three harmonics as much as possible. In addition, the figure of merit of the filter is also very important, so it is recommended to take 0Paint 0 paint, the calculation of second-order filter parameters is more complicated, it is recommended to ** a filter design software, such as TI's Filtpro.

(1) Find the spectrum x (w) of the signal and the frequency characteristic h (w) of the filter, that is, transform them into the frequency domain.

2) Multiplication in the frequency domain, i.e., y(w)=x(w)*h(w), which is equivalent to convolution in the time domain. (piecewise convolution can be used).

3) Inverse convert y(w) to y(n) in the time domain, and the filter is a device used to eliminate interference noise, and the input or output is filtered to obtain pure alternating current. You can derive the most versatile filter types from basic filter building blocks --- second-order general-purpose filter transfer functions: low-pass, band-pass, high-pass, band resistance, and elliptical filters.

The use of MATLAB to design filters has turned the original very cumbersome and complex program design into a simple function call, which has opened up a broad world for the design and implementation of filters, especially the MATLAB toolbox enables researchers in various fields to carry out scientific research and engineering applications intuitively and conveniently. Among them, the signal processing toolbox, image processing toolbox, wavelet toolbox, etc. provide the possibility for the vigorous development of digital filtering research. The MATLAB Signal Processing Toolbox provides an excellent auxiliary design tool for filter design and analysis, and is good at using MATLAB to assist in the design of digital filters, which can greatly improve the design efficiency.