1.13 NeuroSolutions Examples

1.1 The Linear Processing Element in NeuroSolutions

1.2 Computing the MSE for the Linear PE

1.3 Finding the Minimum Error by Trial and Error

1.4 Plotting the Performance Surface

1.5 Comparison of Performance Curves for Different Data Sets

1.6 Adapting the Linear PE with LMS

1.7 Batch versus On-line Adaptation

1.8 Robustness of LMS to Noise

1.9 Estimating the Correlation Coefficient During Learning

1.10 The Learning Curve

1.11 Weight Tracks

1.12 Linear Regression without Bias

1.13 Rattling

1.14 Scheduling of Step Sizes

1.15 Multivariable Regression

1.16 Checking the LMS Solution with the Optimal Weights

1.17 Visualizing the Weight Tracks and Speed of Adaptation

1.18 Visualizing Weight Tracks with On-Line Learning

1.19 Linear Regression Without Bias

1.20 Newton's Method

1.21 Linear Regression Project

Go to next section