Fir Filters For Technologists, Scientists, And Other Non Ph.D.S

The digital filter used most often in digital signal processing (DSP) is the Finite Impulse Response (FIR) filter because it is the easiest to design and it is always stable. An interesting demonstration of the design and implementation of a FIR filter can be shown using MATLAB. The Remez function in MATLAB can be used to generate the filter coefficients for the lowpass, highpass, bandpass, or bandstop filter. MATLAB can be used to generate a set of sinusoidal signals that can be observed in the time domain and frequency domain. The appropriate filter can be applied to pass or block one or all the signals. In addition, MATLAB provides a graphic user interface tool, the Filter Design and Analysis Tool (fdatool), that can be used to generate the filter coefficients. Regardless of the method, the design and implementation of a FIR filter is shown to be straightforward. INTRODUCTION Human reality revolves around the analog domain where perception of events is formed by information that can take on any numeric value at any time. Unfortunately, most modern information is collected, manipulated, collated, and stored in the digital domain associated with computers where data must be a discrete value having limited values for specific times only (Figure 1). The general scheme for converting from the analog domain to the discrete (digital) domain is shown in Figure 2. Digital signal processing (DSP) generally consists of an antialiasing filter to limit the bandwidth of the analog signal, an analog-to-digital converter (ADC) that converts analog signals to discrete signals that the computer or microcontroller can use, a DSP chip that manipulates (filters) the digital signal, a digital-to-analog converter (DAC) to convert the digital Page 14632.2 signal back to an analog signal, and a reconstruction filter to reduce the discontinuities associated with digital-to-analog conversion. The manipulation of data is demonstrated in Figure 3. Figure 1: Analog and digital functions. Figure 2: The general scheme of DSP. P ge 14632.3 Figure 3: An example of DSP. Because digital signal processing is so pervasive in modern applications, Figure 4, all students throughout the electrical engineering spectrum need a general working Figure 4. DSP applications. knowledge of digital filters. The objective is to present such knowledge in a way that technologists, scientists, and other non-PhDs are not frightened by the mathematical rigor of the subject. The most straightforward method of digital signal processing is the FIR filter, and the most straightforward method to mask the mathematical rigor is to use MATLAB 1 .