In this paper Kaiser presented empirical formulae for calculating the shape parameter of the Kaiser-Bessel window required to achieve a desired stop band side lode attenuation. Kaiser, "Nonrecursive digital filter design using I 0-sinh window function". #Digital filter designer generatorThe methods used in this FIR generator were taken from the paper by J. #Digital filter designer codeThe actually algorithm and the JavaScript code to implement it are presented at the bottom of the page.įIR Listing Kaiser-Bessel filter design formulae The filter coefficients are calculated and plotted along with a graph of the frequency response of the filter. Then press the "CALCULATE FILTER" button. To use it, set the sample rate (1kHz < Fs < 1MHz) and the type of filter desired low pass, band pass or high pass, then set the number of points in the filter (N < 500) then set the frequency of ideal filter edges (Fa, Fb) and the minimum attenuation (Att) required in the stop band. To demonstrate the power and simplicity of this technique, a Kaiser-Bessel filter generator is provided below. The Kaiser-Bessel window function is simple to calculate and its parameters can be adjusted to produce the desired maximum side lobe level for a near minimal filter length. This will increase the width of the transition region between the pass and stop bands but will lower the side lobe levels outside the pass band. To suppress the side lobes and make the filter frequency response approximate more closely to the ideal, the width of the window must be increased and the window function tapered down to zero at the ends. Rectangular windowing in the time domain will result in a frequency spectrum with the width of the pass band close to the desired value but with side lobes appearing at the band edges (the effects of time domain windowing on the frequency spectrum are discussed in more detail in the Spectrum Analyser page). The simplest window function is the rectangular window which corresponds to truncating the sequence after a certain number of terms. To create a Finite Impulse Response (FIR) filter, the time domain filter coefficients must be restricted in number by multiplying by a window function of a finite width. Unfortunately, the filter response would be infinitely long since it has to reproduce the infinitely steep discontinuities at the band edges in the ideal frequency response. The filter impulse response is obtained by taking the Discrete Fourier Transform (DFT) of the ideal frequency response. To view the filter coefficients, click the Table or Plot buttons.The basic idea behind the Window method of filter design is that the ideal frequency response of the filter is equal to 1 for all the pass band frequencies, and equal to 0 for all the stop band frequencies. Then, click the Make Filter button to create the filter, using the specified parameters, and to plot the frequency response of the filter. Select the number of filter elements, the cut-off frequencies, and the filter type. This section allows you to design different types of filters. The sampling frequency is extracted from the file, and once the file is loaded, the time and frequency responses are plotted. To load a WAV file as the input signal, click the Load File button, which will open a file dialog box. After the impulse response has been truncated, shifted, and sampled, the FIR filter coefficients are shown in red. The diagram indicates the impulse response in blue. An ideal filter has the impulse response defined by the sinc function: sin x x For example, consider the low pass filter. If the impulse response is nonzero for negative time (the filter is anti-causal) the response must also be shifted to the right until all of the impulse response coefficients are located in the positive time region. The infinitely long impulse response must be truncated to be implemented. The effect of the filter is displayed in a frequency domain.įinite Impulse Response (FIR) Filter DesignĪ FIR filter is derived from the impulse response of the desired filter and then sampled to convert it to a discrete time filter. Four different types of filters are illustrated: low pass, high pass, band pass, and band stop. A Finite Impulse Response (FIR) filter is designed and applied to an input signal stored in a file.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |