DSPRelated.com

The History of CIC Filters: The Untold Story

Rick LyonsRick Lyons February 20, 20126 comments

Hogenauer's 1981 paper is the canonical CIC reference, but this post uncovers an earlier, practical origin story: engineer Richard Newbold used and documented a CIC decimation filter in late 1979. Rick Lyons recounts how Newbold’s HP-35 calculations produced the now-familiar frequency-response plot that appeared in Hogenauer's paper, why managers feared a pole at DC, and how demonstrations won adoption.


Design study: 1:64 interpolating pulse shaping FIR

Markus NentwigMarkus Nentwig December 26, 20115 comments

Markus Nentwig presents a practical 1:64 root-raised cosine interpolator built from cascaded FIR stages that slashes computational cost. By separating pulse shaping from rate conversion, designing each interpolator to suppress only known alias bands, and equalizing the pulse shape, the design achieves just 4.69 MACs per output, roughly 12 percent of a straight polyphase implementation while meeting EVM targets.


Bank-switched Farrow resampler

Markus NentwigMarkus Nentwig August 13, 20112 comments

Markus Nentwig proposes a bank-switched variant of the Farrow resampler that breaks each impulse-response segment into multiple sub-segments, enabling accurate interpolation with lower-order polynomials and fewer multiplications per output. This trades increased total coefficient storage for computational savings. The post explains the concept, connects it to polyphase FIR interpolation, and provides Matlab/Octave and C example code for practical evaluation.


Do Multirate Systems Have Transfer Functions?

Rick LyonsRick Lyons May 30, 20113 comments

Multirate systems can fool you into thinking standard z-domain analysis always applies. Rick Lyons shows why CIC decimation and Hogenauer implementations do not have a single z-domain transfer function from the input to the downsampled output, because downsampling breaks the one-to-one frequency mapping of LTI systems. Use the cascaded-subfilter H(z) up to the decimation point, then explicitly account for aliasing when predicting the decimated spectrum.


Spectral Flipping Around Signal Center Frequency

Rick LyonsRick Lyons November 7, 20075 comments

Most DSP engineers know that multiplying a real signal by (-1)^n inverts its spectrum about fs/4, but that trick fails when you need to flip around a specific carrier. Rick Lyons presents two practical techniques: a multirate upsample-by-two solution using paired lowpass filters and cosine mixing, and a computationally heavier complex-multiply plus real-part method attributed to Dirk Bell, both yielding the desired fcntr-centered flip.


Interpolator Design: Get the Stopbands Right

Neil RobertsonNeil Robertson July 6, 20236 comments

In this article, I present a simple approach for designing interpolators that takes the guesswork out of determining the stopbands.


Decimators Using Cascaded Multiplierless Half-band Filters

Neil RobertsonNeil Robertson November 19, 2023

In my last post, I provided coefficients for several multiplierless half-band FIR filters. In the comment section, Rick Lyons mentioned that such filters would be useful in a multi-stage decimator. For such an application, any subsequent multipliers save on resources, since they operate at a fraction of the maximum sample frequency. We’ll examine the frequency response and aliasing of a multiplierless decimate-by-8 cascade in this article, and we’ll also discuss an interpolator cascade using the same half-band filters.


Compute Images/Aliases of CIC Interpolators/Decimators

Neil RobertsonNeil Robertson November 1, 20202 comments

CIC filters provide multiplier-free interpolation and decimation for large sample-rate changes, but their images and aliases can trip up designs. This post supplies two concise Matlab functions and hands-on examples to compute interpolator images and decimator aliases, showing spectra and freqz plots. Readers will learn how interpolation ratio and number of stages alter passband, stopband, and aliasing behavior.


Multi-Decimation Stage Filtering for Sigma Delta ADCs: Design and Optimization

AHMED SHAHEINAHMED SHAHEIN March 1, 20176 comments

A Matlab toolbox streamlines the design and optimization of multi-stage decimation filters for sigma-delta ADCs. MSD-toolbox automates stage-count and decimation-factor selection, generates Parks-McClellan equiripple FIR coefficients, and iteratively selects coefficient quantization to meet in-band noise constraints. It accepts sigma-delta bitstream stimuli for spectral and intra-stage analysis, includes cost estimation routines, and is published open-source on MathWorks with examples and a dissertation reference.


'z' as in 'Zorro': Frequency Masking FIR

Markus NentwigMarkus Nentwig October 2, 2012

Markus Nentwig shows an efficient way to build steep wideband FIR filters by combining upsampled and complementary stages, then masking their spectra. He provides a Matlab and Octave design program that uses a generic least-squares optimizer to place coefficients, letting you explore filter sizes and oversampling while cutting computational cost significantly compared to a conventional symmetric FIR.