Counterparty Credit Risk and CVA
Compute the unilateral credit value (valuation) adjustment (CVA) for a bank holding a portfolio of vanilla interest rate swaps with several counterparties. CVA is the expected loss on an over-the-counter contract or portfolio of contracts due to counterparty default. The CVA for a particular counterparty is defined as the sum over all points in time of…
Introduction to MIMO Systems
Multiple-Input-Multiple-Output (MIMO) systems, which use multiple antennas at the transmitter and receiver ends of a wireless communication system. MIMO systems are increasingly being adopted in communication systems for the potential gains in capacity they realize when using multiple antennas. Multiple antennas use the spatial dimension in…
This product allows users to interactively design a tabular expression. The resusulting function can be saved as a Simulink block or to a Matlab m-file. Tabular Expressions can be proved to be disjoint and complete using the PVS theorem prover. This allows users to ensure that the table they are designing has covered all possible inputs and is deterministic.
Demo file for batchpleas.m
batchpleas is a wrapper for lsqnonlin, allowing it to solve many small problems (all with the same parameterization) in one batched, partitioned nonlinear least squares estimation. This takes advantage of economies of scale, so as to gain a higher throughput overall. The gain can be dramatic.
Computational cost for Cramer's rule
There are plenty of direct and iterative methods to solve a linear algebraic system of equations. Using Cramer's rule, one can easily obtain the solution for small systems by hand. However, with the growth of the unknowns, the method becomes computationally very expensive. Moreover, calculating a determinant by its definition may result in overflow or underflow if someone wanted to apply it on a computer. That is why Cramer's algorithm is not applied in computations.
Radar Tracking Using MATLAB Function Block
This example shows how to use an extended Kalman filter with the MATLAB® Function block in Simulink® to estimate an aircraft's position from radar measurements. The filter implementation is found in the MATLAB Function block, the contents of which are stored in the Simulink model itself.
Simulating Automatic Climate Control Systems
This example shows how to simulate the working of an automatic climate control system in a car using Simulink® and Stateflow®. You can enter a temperature value you would like the air in the car to reach by double clicking the User Setpoint in Celsius Block and entering the temperature value. You can also set the External Temperature in Celsius in a similar way. The numerical display on the right-hand side of the model shows the reading of a temperature sensor placed behind the driver's head. This is the te
Modeling a Fault-Tolerant Fuel Control System
This example shows how to combine Stateflow® with Simulink® to efficiently model hybrid systems. This type of modeling is particularly useful for systems that have numerous possible operational modes based on discrete events. Traditional signal flow is handled in Simulink while changes in control configuration are implemented in Stateflow. The model described below represents a fuel control system for a gasoline engine. The system is highly robust in that individual sensor failures are detected and the cont