| AbstractNeuron | Implementation helper for common types of Neurons |
| ArgParser | |
| CenterNeuron | A center-neuron, the building block of a Radial basis function network |
| DynamicKohonenParameters | |
| EucledianTopology | Standard eucledian topology OPT: zounds |
| Exception | A common exception class used by all classes in the annie library |
| ExKohonenDraw | |
| File | The idea is that this class will be used to read in information from text files created by the "save" function in various annie classes |
| GABNeuron | Neuron for Gain Adaptive BP |
| HopfieldBase | A Hopfield network - content addressable memory and energy |
| HopfieldBase::NData | |
| HopfieldNetwork | A "standard" incarnation of the Hopfield network usable form most purposes |
| Image | One image (actually a SDL_Context wrapper ..) |
| Image::Color | Color components should be in [0, 1] |
| ImageCompressor | (usually lossy) image compressor |
| ImageCompressor::PartialListener | |
| InputLayer | A layer of input neurons |
| InputNeuron | Input neurons are slightly special |
| KohonenAnalyzer | |
| KohonenAnalyzer::Outs | |
| KohonenDraw | Draws examples and progress of the Kohonen clustering using OpenGL --> Should be called from the redraw thread |
| KohonenNetwork | Todo: getOutput (&& getWin*) doesn't give anything sensible in this impl |
| KohonenNeuron | |
| KohonenParameters | Note: it is closely tied to Topology - the meaning NeighborhoodSize depends on the Topology used |
| Layer | Abstraction for a "layer" of neurons, i.e., a group of neurons not connected to each other |
| Link | Abstraction of a connection between two neurons |
| Matrix | A class for 2-dimensional matrices |
| MLPCompressor | Yeah, yeah - ValueUpdateListener should have been inner class |
| MLPKohonenAnalyzer | Analyzes MLP using Kohonen |
| MultiLayerNetwork | Abstraction of a multi-layer perceptron network |
| MultiLayerNetwork::Error | Error summator will be moved up for general use. |
| Network | Another core class of the annie library, a generic template for a neural network |
| Neuron | One of the fundamental annie classes - the basic Neuron |
| NumberParameter | |
| ParametrizedNeuron | Neuron with a parametrized activation function |
| RadialBasisNetwork | A Radial Basis Function Neural Network |
| RecurrentNetwork | RN constructed from a genotype |
| RecurrentNeuron | A neuron used for recurrent networks |
| Redrawer | |
| RigidVisualiser | Simple text-mode visualiser, which prints updated value after each change (synchronous) |
| Selector | Select features from the TS vectors |
| Shrinker | |
| Shuffler | Shuffles the given training set every nth epoch |
| SimpleNeuron | A simple perceptron - i.e., it takes as input the weighted sum of the outputs of the neurons connected to it |
| SimpleVisualiser | Simple text-mode visualiser, which prints updated value after each change (synchronous), it it didn't occur too soon |
| StandardKohonenParameters | LearningParam = e ^ (- slope * ( ln (time) ^ 2 ) ) neighborHoodSize = (MAX_NB_SIZE) * learningParam |
| StaticKohonenParameters | Static kohonen parameters - don't change unless changed by the user |
| Stepper | Waits for keypress on each "epoch" if "stepped" is true |
| StringParameter | Also holds the destination |
| TerminatedException | |
| TileCompressor | Compress image by dividing it to squares |
| TLayer | Nice getters.. |
| Topology | Class used as a template to the KohonenNetwork network |
| TrainingSet | This is an abstraction for the set of patterns which are used to "train" a network |
| TSTransformer | 2 vectors -> 2 vectors |
| TwoLayerNetwork | Two layered networks are very commonly used |
| Vector | |
| Video | Video (and input) system maintaince |
| Video::Redrawer | User redraw class. draw() will be called from the video thread |
