DADiSP / Filters Overview
Digital Filter Design Module
DADiSP Filters software module is a menu-driven module for FIR and IIR digital filter design and analysis. From any DADiSP Worksheet you can quickly design, view and analyse both FIR (Finite Impulse Response) and IIR (Infinite Impulse Response) filters. Once you have designed a filter, you may filter the raw data then view and analyse the filtered signal. Through the easy-to-use dialogue boxes or simple one line functions you can tune the filter iteratively re-filtering the data until you have separated the signal from the noise cleanly.
- Simple user interface.
- Lowpass, highpass, bandpass, bandstop and multiband filters.
- Finite Impulse Response (FIR) filter design.
- FIR Hilbert transforms and differentiators.
- FIR Remez exchange and Kaiser window design algorithms.
- Infinte Impulse Response (IIR) filter design.
- IIR Bessel, Butterworth, Chebychev I, Chebychev II and Elliptic filters.
- IIR Bilinear Transform and Matched Z design algorithms.
- Magnitude, phase, group delay and impulse response.
- Output coefficent rorm conversion.
- Output coefficent quantisation.
- Time and frequency domain filtering functions.
- Pole-Zero plots.
DADiSP/Filters Version 5.0 includes a completely redesigned user interface to streamline the process of designing and applying digital filters. Straightforward dialogue boxes with automatic option validation simplifies both the design and analysis of filters.
Filter coefficients can be easily converted to various filter structures and quantisation routines are included to help simulate DSP chipsets.
IIR Bessel filters and the Matched Z Transform design method have been added. Linear phase FIR Kaiser filters have been expanded and enhanced. Both time and frequency domain filtering routines have been optimised to provide more efficient filter processing.
Filters 5.0 new features summary
- Streamlined interface.
- IIR Bessel filters.
- IIR Matched Z Design Algorithm.
- Improved FIR Kaiser Window Filters.
- Coefficient Conversion and Quantisation.
- Optimised Filter Processing Functions.
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