Introduction

The importance of digital filters is well established. Digital filters, and more generally digital signal processingalgorithms, are classified as discrete-time systems. They are commonly implemented on a general purpose computeror on a dedicated digital signal processing (DSP) chip. Due to their well-known advantages, digital filters are oftenreplacing classical analog filters.
In this application note, we introduce a new digital filter design and analysis toolimplemented in LabVIEW with which developers can graphically design classical IIR and FIR filters, interactivelyreview filter responses, and save filter coefficients. In addition, real-world filter testing can be performed within thedigital filter design application using a plug-in data acquisition board.Digital Signal Processing (DSP) affords greater flexibility, higherperformance (in terms of attenuation and selectivity), bettertime and environment stability and lower equipment productioncosts than traditional analog techniques. Additionally, more andmore microprocessor circuitry is being displaced with costeffectiveDSP techniques and products; an example of this isthe emergence of DSP in cellular base stations.
Componentsavailable today let DSP extend from baseband to intermediatefrequencies (IFs). This makes DSP useful for tuning and signalselectivity, and frequency up and down conversion.These new DSP applications result from advances in digitalfiltering. This Application Note will overview digital filtering byaddressing concepts which can be extended to basebandprocessing on programmable digital signal processors.