Matlab-AI MATLAB coding assistant

Example

Solve Ax = b: A = [3 2;1 4]; b = [5;6]; x = A\b; % uses efficient factorization Compute eigenvalues: vals = eig(A); Compute SVD: [U,S,V] = svd(M);

Scenario

Structural analysis: assemble a stiffness matrix from finite elements and solve for displacements; compute modal shapes via eigen decomposition for vibration analysis.

Example

t = 0:0.01:2*pi; y = sin(t); plot(t,y,'LineWidth',2); xlabel('t'); ylabel('sin(t)'); imagesc(I); colormap(gray); colorbar;

Scenario

Sensor-data exploration and reporting: overlay multiple time series, create heatmaps of parameter sweeps, produce publication-ready figures or interactive dashboards for stakeholders.

Example

[t,y] = ode45(@(t,y) -2*y + sin(t), [0 10], 1); sol = pdepe(m,@pdefun,@icfun,@bcfun,x,t);

Scenario

Modeling chemical kinetics or biological populations using ODEs; solving heat diffusion or fluid flow approximations with built-in PDE solvers.

Example

x0 = [0;0]; opts = optimoptions('fmincon','Display','off'); [x,fval] = fmincon(@(x) myCost(x), x0, Aineq, bineq, [], [], lb, ub, [], opts); curve = fit(xData,yData,'poly2');

Scenario

Parameter estimation for a physical model (fit parameters so model output matches measured data); constrained design optimization for engineering components.

Example

N = length(x); X = fft(x); f = (0:N-1)*(fs/N); plot(f,abs(X)); d = designfilt('bandpassiir','FilterOrder',4,'HalfPowerFrequency1',0.5,'HalfPowerFrequency2',40,'SampleRate',fs); xFilt = filtfilt(d,sig);

Scenario

Filtering and spectral analysis of ECG/EEG recordings; designing audio filters or removing noise from sensor channels before feature extraction.

Example

I = imread('cells.png'); BW = imbinarize(rgb2gray(I)); stats = regionprops(BW,'Area','Centroid'); imshow(I); hold on; plot([stats.Centroid]);

Scenario

Automated inspection on manufacturing lines (detect defects), medical imaging workflows (segmentation and measurement of structures), or object detection pipelines using pretrained detectors.

Example

Mdl = fitcsvm(X,y,'KernelFunction','rbf'); cvMdl = crossval(Mdl,'KFold',5); [idx,C] = kmeans(X,3); [coeff,score] = pca(X);

Scenario

Customer segmentation (clustering), classification of anomalies, building cross-validated predictive models for churn, credit risk scoring, or forecasting.

Example

net = resnet50; lgraph = layerGraph(net); % Replace final layers and fine-tune netTransfer = trainNetwork(augmentedDatastore, newLayers, options);

Scenario

Image classification for medical diagnosis, transfer learning for defect detection, sequence models for time-series prediction using LSTMs.

Example

G = tf(1,[0.1 1]); step(feedback(G,1)); [A,B,C,D] = ssdata(sys); K = lqr(A,B,Q,R); % state-feedback % Build and simulate controllers in Simulink with real-time parameters

Scenario

Designing controllers for automotive or aerospace applications; simulating and validating control loops before embedded deployment; using Simulink for model-based design and hardware-in-the-loop testing.

Example

syms x t f = sin(x)/x; simplify(diff(f,x)); F = laplace(exp(-2*t), t, s);

Scenario

Deriving closed-form transfer functions, performing symbolic integration or differentiation for analytic insight, or generating formulas used in documentation and teaching.

Example

p = parpool(4); parfor i=1:N results(i) = heavyCompute(i); end % GPU example A_gpu = gpuArray(rand(1000)); B = fft(A_gpu); B_cpu = gather(B);

Scenario

Speed up Monte Carlo simulations, parameter sweeps, large matrix operations, or neural-network training using multiple CPU cores or GPUs without rewriting algorithms in low-level languages.

Example

% Prepare function for code generation %#codegen function y = myfilter(x) y = filter([1 -0.95],1,x); end % Then: codegen myfilter -args {zeros(100,1)} % Create a standalone executable mcc -m myApp.m

Scenario

Generate optimized C code for embedded controllers, produce standalone desktop executables for non‑MATLAB users, or package algorithms as shared libraries callable from other languages.

Example

app = uifigure('Name','Parameter Explorer'); btn = uibutton(app,'Text','Run'); btn.ButtonPushedFcn = @(btn,event) runSimulation(); % Alternatively design interactive apps in App Designer and export as .mlapp

Scenario

Create internal tools so domain experts can run parameter sweeps, visualize results, and export reports without writing code; deliver research tools to collaborators.

Example

T = readtable('measurements.csv'); T.Time = datetime(T.Time,'InputFormat','yyyy-MM-dd HH:mm:ss'); % For huge CSVs: ds = tabularTextDatastore('largefile.csv'); t = tall(ds); summary(t);

Scenario

Ingest and preprocess time-series from IoT devices, merge heterogeneous logs, work with datasets larger than memory using tall arrays or datastores.