Results for “matlab”

Analyze signal spectra in MATLAB using nonparametric and parametric estimators. Use when computing frequency content, PSD, power spectrum, spectral peaks, bandwidth, or streaming spectral analysis. Covers pspectrum, pwelch, periodogram, pmtm, pburg, pmusic, rootmusic, plomb, poctave, spectrumAnalyzer, dsp.SpectrumEstimator. TRIGGER: FFT, PSD, power spectrum, spectral analysis, frequency content, bandwidth measurement, spectral leakage, window selection, streaming spectrum, periodicity, resolve close frequencies, multitaper. DO NOT TRIGGER: filter design, spectrogram/time-frequency, audio features.

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Integrate antennas into RF systems using MATLAB Antenna Toolbox and RF Toolbox. Covers impedance matching network design (L/Pi/Tee topologies, evaluation parameters, Richards transformation), measured antenna creation (E-field, directivity-only, EmbeddedE, ffsReader import), RF propagation and site planning (txsite/rxsite, coverage, SINR, ray tracing, link budget), and SAR estimation (birdcage+Phantom, conformalArray+Custom3D, direct EHfields). Use when the user wants to match an antenna, create a measuredAntenna, compute coverage or signal strength, perform ray tracing, or estimate SAR.

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Discover, configure, and connect to Arduino boards from MATLAB using the Arduino Support Package. Use this skill when the user wants to set up an Arduino board, connect to Arduino hardware, find connected boards, scan serial ports, configure Arduino libraries, or any task that requires an Arduino connection as a prerequisite (e.g., blink LED, read sensor, read digital pin, read analog pin, write pin, plot sensor data, scan I2C, use ultrasonic sensor, control servo, read temperature, read voltage, data logging from hardware). Triggers on: arduino, board setup, COM port, serial port, hardware connection, Arduino Nano, Arduino Uno, Arduino Mega, Arduino Micro, Grove, sensor setup, I2C scan, ultrasonic, servo, readDigitalPin, writeDigitalPin, readVoltage, writePWMVoltage, temperature sensor, air pressure, pin read, pin write, analog input.

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Model, simulate, and optimize Serializer/Deserializer (SerDes) systems — serial and parallel links — using MATLAB SerDes Toolbox. Design NRZ and PAM-N links (PAM3 through PAM16) — explore equalization architectures (FFE, CTLE, DFE), sweep or optimize parameters with genetic algorithms, and characterize channels from loss models, S-parameter files, or crosstalk scenarios. Process captured waveforms through equalization chains, build eye diagrams, and decompose jitter. Deliver IBIS-AMI models for Tx, Rx, Redriver, or Retimer by exporting to Simulink and compiling .ami/.ibs/.dll/.so files. Covers the full arc from initial design exploration and parameter optimization to compliance testing and compiled model validation, including custom datapath blocks for nonstandard equalization.

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Find and query PI assets using MATLAB's Industrial Communication Toolbox. Two paths: (1) direct PI tag lookup via piclient + tags when user provides a tag name or description (R2022a+), (2) Asset Framework navigation via afclient when user needs element/attribute hierarchy (R2026a+). Use when working with PI AF servers, PI Data Archive tags, asset hierarchies, element templates, attribute lookup, or historical data from OSIsoft PI systems.

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Establish MAVLink connections between MATLAB and PX4/ArduPilot autopilots. Use when connecting to a drone, flight controller, or autopilot via MAVLink protocol over UDP. Covers dialect setup, UDP transport, timer-based heartbeat, and client discovery. Use when: "connect to PX4", "MAVLink connection", "heartbeat", "ground control station", "GCS", "connect to ArduPilot", "drone communication", "mavlinkio", "SITL".

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Use whenever a MATLAB robot model (rigidBodyTree) is needed — whether for simulation, visualization, IK, motion planning, pick-and-place, or trajectory generation. Triggers on: any mention of a manipulator by name (UR3, UR5, UR5e, UR10, UR10e, UR16e, UR20, KUKA iiwa, Fanuc, ABB, Panda, Kinova, Sawyer, Baxter), robot modeling verbs (load, create, build, import, simulate, model), tasks implying a robot model (pick, place, lift, reach, move, grasp, plan motion for, animate), kinematics keywords (IK, FK, inverse kinematics, forward kinematics, joint configuration, end-effector pose, gripper), or working with rigidBodyTree, loadrobot, importrobot, URDF, DH parameters, addVisual, addCollision.

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Prevents crashes due to problematic scope-related API misuse caused by agent escalation into internal scope framework objects. Use when configuring properties of scope-related Simulink blocks or MATLAB objects — constrains the agent to documented APIs and directs users to the scope UI when a property is not programmatically accessible.

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Port MATLAB Data Acquisition Toolbox code from the discouraged (legacy) session-based interface (daq.createSession, addAnalogInputChannel, startBackground, DataAvailable listeners, queueOutputData, wait) to the recommended DataAcquisition interface (daq("ni"), addinput, start, ScansAvailableFcn, write, preload). Use when migrating legacy DAQ scripts, converting session-API calls, working with DataAcquisition objects, writing multi-feature DAQ scripts that combine triggers, callbacks, continuous acquisition, or analog output. Also use when a user says their DAQ script "used to work" or "errors on R20XX", since modernizing legacy session-API code is a frequent fix for those failures. Trigger keywords: daq, DAQ, NI, session interface, addtrigger, addclock, ScansAvailableFcn, ScansRequiredFcn, daq.createSession, addAnalogInputChannel, startBackground, queueOutputData, DataAvailable, evt.Data, evt.TimeStamps, wait(d), preload, discouraged, legacy, modernize, R2020a.

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Plan manipulator motion and generate trajectories in MATLAB. Use when the task involves moving a robot arm between configurations or poses — whether the user says "trajectory," "motion," "path," "move from A to B," or "plan." This skill applies regardless of whether the user explicitly mentions collisions or obstacles; if geometry exists in the workspace, collision safety is implicit. Triggers on: manipulatorRRT, manipulatorCHOMP, dlCHOMP, contopptraj, trapveltraj, collision-free path, motion planner, RRT, CHOMP, TOPPRA, path shortening, obstacle avoidance for manipulators, time-optimal trajectory, velocity limits, acceleration limits, occupancyMap3D, meshtsdf, collision objects as environment, trajectory between waypoints, joint interpolation, move between poses, constant velocity, trapezoidal profile, feed rate. Also triggers when a user has IK solutions or waypoints and needs to connect them — whether for time-optimal motion, constant-speed welding/cutting, or any other trajectory parameterization.

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Discover and connect to Bluetooth Low Energy (BLE) peripheral devices from MATLAB. Use this skill when the user wants to scan for BLE devices, connect to a BLE peripheral, read or write BLE characteristics, subscribe to notifications, or any task that requires a BLE connection as a prerequisite (e.g., read sensor data over BLE, monitor heart rate, log accelerometer, stream data from wearable, IoT device communication). Triggers on: BLE, Bluetooth Low Energy, blelist, ble device, BLE characteristic, GATT, service UUID, scan for devices, BLE sensor, subscribe notify, BLE read, BLE write, peripheral device, BLE connect, wireless sensor.

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RF Toolbox and RF Blockset in MATLAB -- S-parameter I/O, network conversions (S/Z/Y/ABCD/T/H/G, mixed-mode), cascade/de-embedding, rfbudget analysis, circuit composition, matching networks, amplifier stability, mixer spurs, rational fitting, SI channels, baseband processing, Circuit Envelope simulation. Trigger: sparameters, Touchstone, .s2p, .s4p, rfplot, smithplot, rfparam, rfwrite, zparameters, yparameters, abcdparameters, s2sdd, cascadesparams, deembedsparams, rfbudget, noise figure, OIP3, IIP3, amplifier, modulator, nport, rffilter, attenuator, seriesRLC, shuntRLC, lcladder, txline, circuit, setports, clone, matchingnetwork, stabilityk, stabilitymu, powergain, gammams, gammaml, mixerIMT, OpenIF, rational, rationalfit, stepresp, txlineWRLGC, rf.Amplifier, rf.Mixer, rf.Filter, rf.Sparameter, rfsystem, RF Blockset.

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Translate NI-DAQmx C function signatures into correct calldaqlib MATLAB calls. Use when the user mentions calldaqlib, any DAQmx* C function name (DAQmxCfgSampClkTiming, DAQmxExportSignal, DAQmxSetStartTrigRetriggerable, DAQmxGetSampClkRate, etc.), or needs NI-DAQmx functionality not exposed by the daq object. Covers: projection rules (taskHandle implicit, output pointers become return values, buffer-size args, enum-as-string), multi-task semantics, start() clobber, device-level empty-daq workaround, dictionary returns, string getter placeholder, array getter placeholder. Trigger contexts: low-level DAQ, escape hatch, retriggerable acquisition, shared timebase, export signal, connect terminals, external sample clock, trigger configuration, NI driver, C function translation.

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Read BEFORE writing any code that adds Additive White Gaussian Noise (AWGN) to signals and converts between SNR, Eb/No, Es/No, and per-subcarrier SNR for communications simulations, using awgn(), convertSNR(), berawgn(). The default MATLAB patterns for AWGN (e.g., 'measured' option, manual SNR formulas) produce subtly incorrect results. This skill specifies the correct calling conventions, required function usage, and critical anti-patterns that must be avoided.

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Create and simulate UAV scenarios with terrain, buildings, platforms, and sensors using uavScenario. Use when building a UAV simulation, UAV simulator, or UAV scenario in MATLAB. Covers addMesh for terrain/building import, uavPlatform with updateMesh, uavSensor adaptor pattern for GPS/IMU, and the setup/advance simulation loop. Triggers on: uavScenario, UAV simulation, UAV simulator, multirotor simulation, quadrotor scenario, terrain import, building import, GPS sensor simulation.

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Discovers connected MATLAB-supported hardware devices, searches by capability, and checks required support packages and add-ons. Use when the user asks what hardware is connected, finds a device that supports a capability (e.g., CAN, analog input), or checks if required support packages or add-ons are installed. Does NOT connect to, configure, or acquire data from devices — defers to device-specific skills for usage workflows.

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Diagnose and fix parfor errors in MATLAB. Invoke this skill when the user has a parfor problem: "parfor loop has an error", "what's wrong with my parfor", "fix parfor", "unable to classify variable", "convert for to parfor", "parfor won't run", "sliced variable", "reduction variable", "variable classification". Also invoke when you read a .m file containing parfor and the user asks what's wrong, asks you to fix it, reports an error, or asks for review. Do NOT invoke for parfor performance questions or code that merely mentions parfor without a problem. ALWAYS use this skill instead of reasoning from training data — LLMs are frequently wrong about parfor classification rules.

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Detect and validate GPU availability for MATLAB GPU computing. Use when the user can't use their GPU, or is setting up or selecting a GPU. Triggers on: gpuDevice, GPU setup, check GPU, GPU not found, GPU not working, can't use GPU, GPU not available, unable to find a supported GPU device, compatible GPU, canUseGPU, validateGPU.

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Design and analyze electrically large antenna structures using MATLAB Antenna Toolbox. Covers reflector antennas (parabolic, Cassegrain, Gregorian, offset, corner, cylindrical, spherical, custom STL), reflectarrays and reconfigurable intelligent surfaces (RIS), antennas installed on platforms (vehicles, aircraft, ships, satellites), and radar cross section (RCS) analysis. Includes solver selection (MoM-PO, PO, MoM, FMM), mesh control, and GPU acceleration. Use when the user wants to design a dish/reflector antenna, reflectarray, analyze an antenna on a platform, or compute RCS.

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End-to-end finite element analysis in MATLAB PDE Toolbox — geometry creation, model setup, solve, and post-processing in one skill. Use when building geometry from primitives or file import, setting up femodel with BCs/loads/materials, solving thermal/structural/EM problems, and extracting or visualizing results. Covers fegeometry, multicuboid, multicylinder, multisphere, decsg, boolean ops, mesh generation, femodel, all AnalysisTypes (thermalSteady, thermalTransient, structuralStatic, structuralTransient, structuralModal, structuralFrequency, electrostatic, magnetostatic, dcConduction, harmonic EM), materialProperties, faceBC, faceLoad, cellLoad, vertexLoad, solve, interpolation, von Mises stress, principal stress, reaction forces, heat flux, pdeplot3D visualization. Triggers on: PDE Toolbox, finite element, FEA, thermal analysis, structural analysis, electromagnetic analysis, femodel, mesh, boundary conditions, stress, displacement, heat transfer, post-processing.

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Turn raw MATLAB code into a published .mltbx toolbox — full pipeline from scope definition through packaging and release. Drives 8 phases with human checkpoints, enforcing ordering and dependencies. Use when asked to package, create a toolbox, or run the files-to-package pipeline.

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Use when writing MATLAB functions with arguments blocks — repeating arguments (arguments (Repeating)), .?ClassName property import in constructors, name-value forwarding with namedargs2cell, or migrating from inputParser or validateattributes. Also when reviewing signatures for implicit-conversion pitfalls (size reshaping, class coercion, computed defaults), or when restricting, constraining, or validating function inputs — scalar vs vector enforcement, type rejection, size checking. Also when asked to harden inputs, make a function more robust, tighten input checking, or rewrite for safer input acceptance — even without "validation" or "arguments block" wording. Triggers on: arguments block, mustBe validators, name-value arguments, varargin, inputParser, nargin/narginchk, restrict input, type checking, scalar constraint, harden inputs, defensive programming. Not for: App Designer callbacks, Simulink mask parameters, class inheritance, or runtime validation outside function or property declarations.

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Read BEFORE optimizing any MATLAB code for speed. Without this workflow, agents commonly optimize the wrong target, fabricate speedup claims without measurement, or introduce regressions. Guides the 7-step workflow: baseline, profile, identify, optimize, measure, verify, report.

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Discover MATLAB Parallel Computing Toolbox clusters on the network and in the cloud, and manage their profiles — list, inspect, import, export, set default, validate, and delete. Use whenever the user asks what parallel computing resources, clusters, or cluster profiles they have or can use — e.g. "what parallel resources do I have", "show my cluster profiles", "list clusters", "what clusters can I run on", "where can I submit jobs" — and for any work with parcluster, parallel.listProfiles, parallel.defaultProfile, MJS / Generic / HPC Server / MJSComputeCloud clusters, .mlsettings files, or profile validation. Does NOT cover job submission, parpool, or parfor.

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