Fuzzy Auto Guided Vehicle Sample
This sample application demonstrates part of classical robotics application: the navigation of an auto guided vehicle. An artificial vehicle is travailing through artificial environment, which has obstacles/walls and driving space. Collecting information from its three sensors (distance to obstacle on the left, on the right and in front of vehicle), the robot should decide how to correct its movement - which angle to use to rotate. All the robot's logic is represented by fuzzy rules. Once sensors' values are provided as inputs into the system, the fuzzy rules are examined to get the movement angle's correction.
This sample demonstrates genetic computations and introduces Genetic Programming (GP) and Gene Expression Programming (GEP). Using both GP and GEP the sample application tries building an algebraic expression, which approximates the given function specified as data points. For the approximation task, the application allows to specify functions set to use: only simple arithmetic operation or extended set with additional functions. During algorithm's work, the application updates graph showing current solution, so it could be seen how the found expression fits given data points.
Delta Rule Learning
This sample is similar to the above one - it also classifies linearly separable data into several classes, which means that this sample also demonstrates a layer of neurons. But this time neurons have continuous activation function, but not a threshold function, which enables usage of new learning algorithm known as delta rule learning.
Independent Component Analysis (ICA)
Sample application demonstrating how to use Independent Component Analysis (ICA) to perform blind source separation of audio signals.
The sample application demonstrates the work of different motion detection algorithms. With this application it is possible as just to enable/disable motion detection, as turn on different motion post processing algorithms, like highlighting of motion regions. It supports number of different video sources, which includes USB web cameras, JPEG snapshots and MJPEG streams over HTTP (IP cameras), local video files. In addition it allows specifying regions of interest, where the motion should be detected. Yet another feature of this application is to show motion history - a chart on the bottom, which shows history of detected motion level.
Handwritten digits recognition by using Non-linear (Multiple) Discriminant Analysis using Kernels (KDA).
Speech Recognition & Text to Speech
If you are interested in computer text to speech (TTS) and speech recognition (SR), this demonstration is for you, it will demonstrates the speech technologies for more than 26 different languages :