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Unformatted text preview: BME251 Project 1 Neuronal Recordings and Filtering Filters are important in technology these days in removing noise and unwanted parts of a signal at certain frequencies. There are three main types of filters we learned about in this class, namely: Lowpass which allows only parts of a signal at low frequencies to be preserved. Highpass which allows only parts of a signal at high frequencies to be preserved. Bandpass which allows only parts of a signal in the middle to be preserved, cutting off the signal at high and low frequencies. In this project we were given a signal (spikes.mat), which is a recording of a neurons activity. The recording was very noisy and needed filtering. This was done using each of the three filter types at different stopband and passband frequencies. A Butterworth filter of each type was created then plotted using Matlab. To do this we created a function in Matlab which took seven inputs: the signal needing to be filtered, the type of filter wanted to be used, digital passband frequency, digital stopband frequency, stopband attenuation, passband error, and sampling frequency. All of these inputs were entered by the user and processed by Matlab which outputted a filtered signal. For this project we learned to use three Matlab functions which are specifically used for Butterworth filters, they are buttord(), butter(), and filter(). Buttord() is used to find the order and cutoff frequency of the filter with inputs being passband frequency, stopband frequency, passband error, and stopband attenuation. Butter() takes the order and cutoff frequency, found using buttord(), and the type of filter inputted by the user and outputs two coefficients for a digital Butterworth filter. Filter() takes the coefficients from butter() and the inputted signal, which needs filtering, and applies the digital Butterworth filter outputting a finished signal which is the result of this project. To create this filter we will create a function in an M-file, using the three functions discussed, we will call this function butterworth(), seeing as we are creating a butterworth filter. This function will take the seven inputs digital: digital passband frequency(fp)- Entered in hertz as one number for high and lowpass filters and as two numbers for bandpass filters. digital stopband frequency(fs)- Entered in hertz as one number for high and lowpass filters an as two numbers for bandpass filters. stopband attenuation(rs)- Entered in dBs as one number. passband error(rp)- Entered in dBs as one number. filter type(filtType)- Entered as a character expression choosing from ‘high’, ‘low’, or ‘bandpass’. input signal(X)- A signal given as a file which is imported into matlab....
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This note was uploaded on 10/01/2008 for the course BME 251 taught by Professor Escabi during the Spring '08 term at UConn.
- Spring '08