Performance Analysis of New Digital Filters in Electronic Information Signal Processing

In order to solve the problems of low signal quality, low transmission and processing efficiency caused by noise interference, signal distortion and frequency band limitation in electronic information signal processing, this paper applies a new digital filter to achieve efficient signal processing through precise frequency domain analysis and filter design. This paper uses Kalman filtering technology to establish a statistical model of signals and noise, update the filter coefficients in real time to adapt to the changes of signals and noise, and uses wavelet transform to perform multi-resolution analysis on the signal to separate the different scale components of the signal, and process these components separately to restore the original signal. By adjusting the filter bandwidth and cutoff frequency, the frequency band range of the signal can be precisely controlled to meet specific application requirements. Through digital signal processing technology, combined with modern filtering techniques such as Kalman filtering and adaptive filtering, this paper demonstrates the significant advantages of new digital filters in improving signal quality and processing efficiency. Finally, the performance of the designed filter is verified through experiments. The experimental results show that the new filter performs particularly well in terms of frequency response, nonlinear distortion, time domain performance and group delay response. In terms of time domain performance evaluation, the new digital filter is superior to other traditional filters in terms of delay time, rise time, peak time and adjustment time. The delay time of the new filter is 2.26 ms, which proves the theoretical superiority of the new filter and also shows its potential in practical applications.