无码激情亚洲一区|日韩人妻在线潮喷视频|老司机一二三区福利视频|亚洲欧美综合精品成人导航|亚洲AV无码久久寂寞少妇|国产午夜亚洲精品不卡福利|久久国产精品99久久人人澡|亚洲国产成人香蕉在线不卡一区

贛州研創(chuàng)電子科技有限公司

YANCHUANG OPTOELECTRONIC TECHNOLOGY(GANZHOU) Co., Ltd

Your location: Home > News > Product News

What is the difference between filters?

Back to list Source: Release Date: 2022-09-22 15:12

The filter circuit is named according to the operating frequency band of the filter circuit: the cutoff frequency is set to fp, and signals with frequencies below fp can pass through. A circuit where signals above fp are attenuated is called a low-pass filter, and signals with frequencies above fp can pass through. The circuit where the signal below fp is attenuated is called a high-pass filter. A band-pass filter is a circuit that passes a signal between a low frequency cutoff and a high frequency cutoff.


Low-pass filters and high-pass filters can be connected in series to form a band-pass filter. As for bandwidth, you can write the transfer function first, replacing the center frequency with the gain that calculates the center frequency, a (w0), and then replacing 0 with the center frequency (w0), solving for the upper and lower frequencies (if you are interested). Anyway, it's not the low-pass cutoff frequency minus the high-pass cutoff frequency. The two cutoff frequencies are 0 times a (0) and 0 times a (infinity), not 0 times the central frequency gain, not 0 times the central frequency gain. There is an inductive output between the inputs of the low-pass filter circuit, and the input and output are respectively grounded through a capacitor. Filtering is the operation of filtering out the specific frequency band in the signal, and is an important measure to suppress and prevent interference. It is a probabilistic theory and method based on observing the results of one stochastic process to estimate another related stochastic process.


The term filter filtering originates from communication theory as a technique for extracting useful signals from received signals containing interference. "Received signal" is equivalent to the observed stochastic process, and "useful signal" is equivalent to the estimated stochastic process. For example, using radar to track aircraft, the measured aircraft position data contains measurement errors and other random disturbances. How to use this data to estimate the position, speed, acceleration, etc. of the aircraft as accurately as possible at each moment and predict the future position of the aircraft is a filtering and prediction problem.