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Code Listing by Yi Cao

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In Evolutionary Multiobjective Optimization (EMO), an algorithm produces a set of points in the performance space as an estimation of the Pareto front. A quantitive measure is desired to estimate the closeness of the estimated data points to the true Pareto front.

One of such measures is the hypervolume indicator, which gives the hypervolume between the estimated Pareto front (P) and a reference point (R). However, to rigorously...



A moving average implementation using build-in filter, which is very fast.



This is the first part of the planned series for Model Predictive Control (MPC) tutorials.

Dynamic Matrix Control is the first MPC algorithm developed in early 1980s. It is probably also the most widely used MPC algorithm in industry...



This is the third part of the work to select measurements / measurement combination for selfoptimizing control. It uses aberage loss as the criterion instead of the worst case loss presented in the second part.

Bidirection branch and...



This is an extremely fast implementation of the famous Hungarian algorithm (aslo known as Munkres' algorithm). The new version (V2.2)is about 1.5 times faster than the old version (V2.1). It can solve a 1000 x 1000 problem in about 20 seconds in a...



The conjugate gradient method aims to solve a system of linear equations, Ax=b, where A is symmetric, without calculation of the inverse of A. It only requires a very small amount of membory, hence is particularly suitable for large scale...



Non-parametric regression is widely used in many scientific and engineering areas, such as image processing and pattern recognition.

Non-parametric regression is about to estimate the conditional expectation of a random variable:



A recursive version of the fast solver to provide more tweak handles for those wish to push the 3-minute limits



Kernel regression is a power full tool for smoothing, image and signal processing, etc. However, it is computationally expensive when it is extented for multivariant cases. The efficiency can be improved by only using neighbors within the...



Nonlinear state estimation is a challenge problem. The well-known Kalman Filter is only suitable for linear systems. The Extended Kalman Filter (EKF) has become a standarded formulation for nonlinear state estimation. However, it may cause...