CVX

Define asset return and covariance matrices.

Specify portfolio constraints (e.g., budget, diversification).

Formulate the optimization problem in CVX to minimize portfolio variance subject to return and constraint requirements.

Solve using CVX to obtain optimal asset weights.

Analyze the resulting portfolio performance.

Define desired filter frequency response.

Specify filter order and structure.

Formulate the filter design problem in CVX to minimize the error between the designed and desired responses.

Solve using CVX to obtain filter coefficients.

Implement the filter and evaluate its performance.

Load training data with features and labels.

Define the SVM model and its parameters.

Formulate the SVM training problem in CVX to maximize margin while minimizing classification error.

Solve using CVX to obtain optimal model parameters.

Evaluate the trained model on test data.

Define the system dynamics and performance requirements.

Specify the controller structure.

Formulate the control design problem in CVX to minimize a cost function subject to stability and performance constraints.

Solve using CVX to obtain controller parameters.

Simulate the closed-loop system to verify performance.

Define available resources and demand requirements.

Specify profit generated by each resource allocation.

Formulate the resource allocation problem in CVX to maximize profit subject to resource and demand constraints.

Solve using CVX to obtain optimal allocation amounts.

Analyze the resulting profit and resource utilization.