Matlab Design Digital Filter

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From the author

Design and validate digital filters in MATLAB. Use when cleaning up noisy signals, removing interference, filtering signals, designing FIR/IIR filters (lowpass/highpass/bandpass/bandstop/notch), or comparing filters in Filter Analyzer.

— the description by MathWorks

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured workflow for designing and validating digital filters within MATLAB. It guides users through signal analysis, architecture selection, and verification, ensuring that filter designs meet specific frequency and magnitude requirements. The skill emphasizes the use of standard MATLAB functions like designfilt and filterAnalyzer, while enforcing best practices for numerical stability and frequency-aware design.

What it does

Designs FIR and IIR filters including lowpass, highpass, bandpass, bandstop, and notch types.
Provides a systematic workflow for signal analysis and architecture selection.
Facilitates visual comparison of filter designs using Filter Analyzer.
Enforces best practices for numerical stability, such as using SOS forms for IIR filters.
Includes validation steps to verify filter performance against specifications.
Supports both streaming and offline filtering implementation strategies.

When to use it

When you need to clean up noisy signals or remove specific interference.
When designing digital filters with specific frequency and ripple requirements.
When comparing different filter architectures like FIR versus IIR.
When working on streaming or batch signal processing pipelines.

Advantages

Ensures consistent design methodology through a preflight and verification checklist.
Promotes numerical stability by recommending specific filter forms.
Integrates directly with MATLAB's signal processing and DSP toolboxes.
Provides clear guidance on handling narrow transition bands.

Usage examples

“Design a lowpass filter for a 1000 Hz signal with a 200 Hz cutoff.”: The agent will ask for the sample rate (Fs), filter mode (streaming vs offline), and phase requirements before generating the design code.
“How do I compare two different filter designs in MATLAB?”: The agent will guide you to use the filterAnalyzer function and provide the necessary steps to visualize and compare their magnitude and group delay responses.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/matlab/matlab-design-digital-filter/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip matlab-design-digital-filter.zip -d .agents/skills

Documentation by MathWorks

Design Digital Filters in MATLAB

Design, implement, and validate digital filters using Signal Processing Toolbox and DSP System Toolbox. Choose the right architecture (single-stage vs efficient alternatives), generate correct code, and verify the result with plots and numbers.

When to Use

Designing lowpass, highpass, bandpass, bandstop, or notch filters
Cleaning up noisy signals or removing interference
Choosing between FIR and IIR filter architectures
Comparing filter designs in Filter Analyzer
Building streaming (real-time) or offline (batch) filtering pipelines
Handling narrow transition bands with multirate or IFIR approaches

When NOT to Use

Adaptive filtering (LMS, RLS) -- use Signal Processing Toolbox docs directly
Audio-specific processing (equalization, room correction) -- use Audio Toolbox
Image filtering (2D convolution, morphological ops) -- use Image Processing Toolbox
General spectral analysis without filtering intent -- FFT/periodogram docs suffice

Key Rules

Read references/INDEX.md before writing any filter design code.
Always write to .m files. Never put multi-line MATLAB code directly in evaluate_matlab_code. Write to a .m file, run with run_matlab_file, edit on error.
Preflight before ANY MATLAB call. Before calling any function listed in INDEX.md, read the required quick-ref first. State Preflight: [files] at the top of the response.
Do not guess key requirements. If Mode (streaming vs offline) or Phase requirement is not stated, ask.
No Hz designs without Fs. If Fs is unknown, stop and ask (unless the user explicitly wants normalized frequency).
Always pin the sample rate. Use designfilt(..., SampleRate=Fs) and freqz(d, [], Fs).
IIR stability: Prefer SOS/CTF forms (avoid high-order [b,a] polynomials).

Preflight Procedure

List MATLAB functions to call
Check references/INDEX.md for each (function-level + task-level tables)
Read required quick-ref files
State at response top: Preflight: quick-ref/filter-analyzer.md, quick-ref/designfilt.md (or Preflight: none required)

Workflow

Phase 1: Signal Analysis

Analyze input data via MCP (spectrum, signal length, interference location)
Compute trans_pct and identify interference characteristics

Phase 2: Clarify Intent

After signal analysis, ask Mode + Phase if not stated:

Mode: streaming (causal) | offline (batch)
Phase: zero-phase | linear-phase | don't-care

Wait for answer before showing any approach comparison or overview.

Phase 3: Architecture Selection

Open references/efficient-filtering.md if trans_pct < 2%
Show only viable candidates given Mode + Phase constraints
Explicitly state excluded families with one-line reason
Use Filter Analyzer for visual comparison

Design Intake Checklist

Required signal + frequency spec (cannot proceed without)

Fs (Hz)
Response type: lowpass / highpass / bandpass / bandstop / notch
Edge frequencies in Hz

If any item is missing, ask.

Required intent for architecture choice (ask if unknown)

Mode: streaming (causal) | offline (batch)
Phase: zero-phase | linear-phase | don't-care
Magnitude constraints: Rp_dB passband ripple (default 1 dB), Rs_dB stopband attenuation (default 60 dB)

If Mode or Phase is unknown, ask 1-2 clarifying questions and stop.

Architecture Checkpoint

Compute and state before finalizing an approach:

trans_bw = Fstop - Fpass
trans_pct = 100 * trans_bw / Fs
M_max = floor(Fs/(2*Fstop)) (only meaningful for lowpass-based multirate)

Decision rule:

trans_pct > 5% -- single-stage FIR or IIR is usually fine
2% <= trans_pct <= 5% -- single-stage possible; mention efficient alternatives if cost/latency matters
trans_pct < 2% -- stop and do a narrow-transition comparison (see references/quick-ref/efficient-filtering.md)

Design + Verify

Feasibility check -- Let designfilt choose minimum order, then query filtord(d). Optionally use kaiserord/firpmord for FIR length estimates.
Design candidates -- Prefer designfilt() with explicit Rp/Rs and SampleRate=Fs. Streaming IIR: use SystemObject=true. Offline zero-phase: filtfilt() is allowed but state that it squares the magnitude response.
Compare visually -- Use filterAnalyzer() for comparing 2+ designs. Read references/quick-ref/filter-analyzer.md first. Minimum displays: magnitude + group delay.
Verify with numbers -- Worst-case passband ripple and stopband attenuation vs spec. For filtfilt(), verify the effective response (magnitude squared).
Deliver the output -- Specs recap, derived metrics, chosen architecture + why, MATLAB code, verification snippet + results, implementation form.

Key Functions

Function	Purpose
`designfilt()`	Primary filter design (FIR and IIR, all response types)
`filterAnalyzer()`	Visual comparison of 2+ filter designs
`freqz()`, `grpdelay()`	Frequency response and group delay analysis
`filtfilt()`	Zero-phase offline filtering
`dsp.SOSFilter`	Streaming IIR via `SystemObject=true`
`designMultirateFIR()`	Multirate decimator/interpolator design
`ifir()`	Interpolated FIR for narrow transitions at constant rate
`cost()`	MPIS (MultiplicationsPerInputSample) on DSP System objects
`kaiserord()`, `firpmord()`	FIR order estimation

Conventions

Always specify SampleRate=Fs in designfilt() and plot in Hz with freqz(d, [], Fs)
Use filterAnalyzer() for multi-filter comparison, not custom freqz/grpdelay plots
Use SOS form for IIR (avoid [b,a] for order > 8)
Use tiledlayout/nexttile for multi-panel figures (not subplot)

Files

ATTRIBUTION.mdAdded by AutoGineer1.0 KiB
LICENSELicence file added by AutoGineer1.4 KiB
SKILL.md6.1 KiB
manifest.yaml473 B
references/INDEX.md2.9 KiB
references/best-practices.md7.8 KiB
references/efficient-filtering.md14.4 KiB
references/filter-analyzer.md18.1 KiB
references/multirate.md13.2 KiB
references/multistage-ifir.md8.5 KiB
references/patterns.md16.2 KiB
references/quick-ref/designfilt.md6.0 KiB
references/quick-ref/efficient-filtering.md6.1 KiB
references/quick-ref/filter-analyzer.md3.0 KiB
references/quick-ref/general-iir-fir.md3.0 KiB
references/quick-ref/multirate-offline.md2.3 KiB
references/quick-ref/multirate-streaming.md3.6 KiB
references/quick-ref/multistage-ifir.md2.8 KiB

references/quick-ref/designfilt.md

designfilt Reference Card

Open this card before writing any designfilt(...) call.

Response Type Quick Reference

Filter type	Response string	Key parameters
Lowpass FIR	`"lowpassfir"`	`PassbandFrequency`, `StopbandFrequency`
Lowpass IIR	`"lowpassiir"`	`PassbandFrequency`, `StopbandFrequency`
Highpass FIR	`"highpassfir"`	`StopbandFrequency`, `PassbandFrequency`
Highpass IIR	`"highpassiir"`	`StopbandFrequency`, `PassbandFrequency`
Bandpass FIR	`"bandpassfir"`	`PassbandFrequency=[f1 f2]` (vector OK)
Bandpass IIR	`"bandpassiir"`	`PassbandFrequency1`, `PassbandFrequency2` (scalar!)
Bandstop FIR	`"bandstopfir"`	`StopbandFrequency=[f1 f2]` (vector OK)
Bandstop IIR	`"bandstopiir"`	`StopbandFrequency1`, `StopbandFrequency2` (scalar!)
Notch (single tone)	`"notchiir"`	`CenterFrequency`, `QualityFactor`
Peak (boost)	`"peakiir"`	`CenterFrequency`, `QualityFactor`, `PassbandRipple`

Core Patterns

FIR (linear phase by default)

d = designfilt("lowpassfir", ...
    PassbandFrequency=Fpass, StopbandFrequency=Fstop, ...
    PassbandRipple=Rp, StopbandAttenuation=Rs, ...
    SampleRate=Fs, DesignMethod="equiripple");

IIR (minimum order)

d = designfilt("lowpassiir", ...
    PassbandFrequency=Fpass, StopbandFrequency=Fstop, ...
    PassbandRipple=Rp, StopbandAttenuation=Rs, ...
    SampleRate=Fs, DesignMethod="ellip");

Notch (single tone removal)

d = designfilt("notchiir", ...
    FilterOrder=2, CenterFrequency=f0, QualityFactor=Q, ...
    SampleRate=Fs);

FilterOrder is required for notchiir — omitting it causes a runtime error. Order 2 (single biquad) is standard; use higher even orders for deeper notches.

Q guidelines: 10-50 typical. Higher Q = sharper notch but more ringing.

Bandpass IIR (scalar edges required!)

d = designfilt("bandpassiir", ...
    StopbandFrequency1=fs1, PassbandFrequency1=f1, ...
    PassbandFrequency2=f2,  StopbandFrequency2=fs2, ...
    PassbandRipple=Rp, ...
    StopbandAttenuation1=Rs, StopbandAttenuation2=Rs, ...
    SampleRate=Fs, DesignMethod="ellip");

Bandstop IIR (scalar edges + numbered ripple!)

d = designfilt("bandstopiir", ...
    PassbandFrequency1=fp1, StopbandFrequency1=fs1, ...
    StopbandFrequency2=fs2, PassbandFrequency2=fp2, ...
    PassbandRipple1=Rp, StopbandAttenuation=Rs, PassbandRipple2=Rp, ...
    SampleRate=Fs, DesignMethod="ellip");

Mirror of bandpassiir: two passbands need PassbandRipple1/2, one stopband uses singular StopbandAttenuation.

Design Methods

Method	Characteristics
`"ellip"`	Minimum order, equiripple in pass & stop
`"butter"`	Maximally flat, monotonic response
`"cheby1"`	Ripple in passband only
`"cheby2"`	Ripple in stopband only
`"equiripple"`	Parks-McClellan (FIR only)

SystemObject=true (streaming)

For streaming applications, get a System object directly:

% Returns dsp.SOSFilter (IIR) or dsp.FIRFilter (FIR)
sosFilter = designfilt("lowpassiir", ...
    PassbandFrequency=Fpass, StopbandFrequency=Fstop, ...
    SampleRate=Fs, DesignMethod="ellip", ...
    SystemObject=true);

y = sosFilter(x);  % Stateful, ready for streaming

Gotchas

IIR bandpass/bandstop vector error

Wrong:

% Anti-pattern
d = designfilt("bandpassiir", ...
    PassbandFrequency=[300 3400], ...);  % ERROR! Vector not allowed for IIR

Correct: Use scalar properties with ...1/...2 suffixes.

Note: FIR bandpass/bandstop CAN use vectors: PassbandFrequency=[f1 f2]

IIR bandpass/bandstop ripple and attenuation naming

Suffix follows the number of bands in minimum-order designs:

bandpassiir (1 passband, 2 stopbands): PassbandRipple + StopbandAttenuation1/2
bandstopiir (2 passbands, 1 stopband): PassbandRipple1/2 + StopbandAttenuation

Using the wrong form (e.g., PassbandRipple for minimum-order bandstopiir, or StopbandAttenuation1/2 for bandstopiir) produces an invalid parameter set error.

Deprecated Coefficients property

Wrong: sos = d.Coefficients; (removed in recent versions)

Correct:

B = d.Numerator;      % Lx3 per-section
A = d.Denominator;    % Lx3 per-section
sos = [B A];          % Lx6 if needed

Manual dsp.SOSFilter vs SystemObject=true

Don't manually extract coefficients to create a System object:

% Template
% Inefficient
d = designfilt(...); B = d.Numerator; A = d.Denominator;
sosFilter = dsp.SOSFilter('Numerator', B, 'Denominator', A);

% Efficient - get System object directly
sosFilter = designfilt(..., SystemObject=true);

Narrow bandpass FIR undershoot

Equiripple minimum-order designs for narrow bandpass filters can undershoot specs — the optimizer distributes error across bands and may exceed Rp or miss Rs.

Fix: Over-design by tightening specs (e.g., Rp×0.5, Rs+5 dB), then verify the actual measured response against the real spec.

% Real spec: Rp=1 dB, Rs=50 dB
% Over-design to compensate for equiripple undershoot:
d = designfilt("bandpassfir", ...
    StopbandFrequency1=150, PassbandFrequency1=180, ...
    PassbandFrequency2=220, StopbandFrequency2=250, ...
    StopbandAttenuation1=55, PassbandRipple=0.5, StopbandAttenuation2=55, ...
    SampleRate=Fs, DesignMethod="equiripple");
% Then verify: freqz(d, [], Fs) and check measured Rp/Rs against REAL spec

Boundary over-spec for minimum-order designs

designfilt minimum-order designs can land exactly on the spec boundary (e.g., measured Rs = 60.0 dB for Rs=60 spec). Over-specify Rs by 1 dB to ensure margin.

Ultra-high-Q notch (excessive ringing)

Problematic: QualityFactor=1000 causes long ringing

Better: Use moderate Q (10-50). For multiple tones, use several moderate notches instead of one ultra-sharp notch.

Legacy notch APIs

iirnotch — deprecated (to be removed). Use designfilt("notchiir") instead.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

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Attribution and licence

Created by

MathWorks

Publisher

MathWorks (Official)

Source

matlab/matlab-agentic-toolkit · skills-catalog/signal-processing/matlab-design-digital-filter · commit 2a7f215

Licence

BSD 2-Clause License (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE.md)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-08

AutoGineer is not affiliated with or endorsed by MathWorks.

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