Class Hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 123]

SharpBCI.ARModel	A simple AR model class which can predict the next value of X given AR parameters (phi), a constant factor (i.e., E[noise(X)]), and previous values of X O(p) performance
SharpBCI.AsyncStreamReader
SharpBCI.AsyncStreamWriter	Used internally to asynchronously write a string to a file stream
System.Numerics.Complex	Patch for lack of System.Numerics
DSPLib.DFT	Performs a complex DFT w/Optimizations for .NET >= 4
DSPLib.DSP
SharpBCI.DummyAdapterSignal	A simple struct which defines a signal of given frequencies and amplitudes (per-channel)
SharpBCI.DynamicTimeWarping
SharpBCI.EEGDeviceAdapter	An abstract base class from which all device adapters should inherit
SharpBCI.CSVReadAdapter	A device adapter that can be used to replay or reemit the data logged during a previous session
SharpBCI.InstrumentedDummyAdapter	An EEGDeviceAdapter which is used to emit a certain set of signals via StartSignal
SharpBCI.DummyAdapter	A version of InstrumentedDummyAdapter which constantly emits a given DummyAdapterSignal Generally used for smoke-testing / debugging your SharpBCI pipeline
SharpBCI.RemoteOSCAdapter	An EEGDeviceAdapter which connects to an EEGDevice via OSC It then asynchronously listens for messages on a given OSC socket and emits the appropriate EEGEvents for the received OSC message Target Hardware: Muse 2014 and Muse 2016 (via android-bridge.apk)
SharpBCI.EEGEvent	A class which represent various types of events relating to EEG data
DSPLib.FFT	Performs an in-place complex FFT
SharpBCI.IArtifactDetector	An interface which defines an abstract artifact detector You can implement this to utilize classes which find the best detector implementation
SharpBCI.ARArtifactDetector	A detector which uses an underlying AR model to detect artifacts
SharpBCI.TournamentArtifactDetector	The TournamentArtifactDetector holds a "tournament" of some number ARArtifactDetectors (termed competitors) The majority consensus of the most well-fit models is the final determination of whether or not the data is an artifact
IDisposable
SharpBCI.ILogOutput
SharpBCI.ConsoleLogger
SharpBCI.FileLogger
SharpBCI.IFilter< T >
SharpBCI.ConvolvingFilter
SharpBCI.ConvolvingDoubleEndedFilter
SharpBCI.ConvolvingSingleEndedFilter
SharpBCI.ExponentialFilter
SharpBCI.MovingAverageFilter
SharpBCI.MultiFilter< T >
SharpBCI.RecursiveFilter
SharpBCI.NarrowPassFilter
SharpBCI.NotchFilter
SharpBCI.IndexableQueue< T >	Weiss implementation of Circular Buffer with addition of indexability
SharpBCI.IPipeable	All components of the SharpBCI pipeline are expected to implement this interface
SharpBCI.IPredictorPipeable	Extends the typical pipeable to include training controls SharpBCI uses these functions to interface with the prediction mechanisms
SharpBCI.AggregatePredictionPipeable	A pipeable which aggregates received EEGEvents into an array based on the reported EEGEvent timestamp and then uses an IPredictor<EEGEvent[]> to train/classify on them
SharpBCI.Pipeable
SharpBCI.AggregatePredictionPipeable	A pipeable which aggregates received EEGEvents into an array based on the reported EEGEvent timestamp and then uses an IPredictor<EEGEvent[]> to train/classify on them
SharpBCI.BandpassPipeable	A pipeable which implements a band-pass filter on all incoming data Input types: EEGEvent Output types: EEGEvent
SharpBCI.EEGDeviceProducer	Wraps an EEGDeviceAdapter with a Pipeable and emits EEGDataType.EEG events Should only be used as a producer not consumer
SharpBCI.FFTPipeable	A Pipeable which performs an FFT on each channel It outputs an FFTEvent every windowSize samples
SharpBCI.RawEventEmitter	An end-point consumer which emits TrainedEvents it received Must only be connected to Pipeables which output EEGEvents
SharpBCI.SimpleFilterPipeable	This pipeable is deprecated and may be removed at any point without warning
SharpBCI.TournamentArtifactPipeable	An artifact detector which uses a TournamentArtifactDectector on a per-channel basis to detect artifacts Input types: EEG, Output types: EEG
SharpBCI.TrainedEventEmitter	An end-point consumer which emits TrainedEvents it received Must only be connected to Pipeables which output TrainedEvents
SharpBCI.IPredictor< T >	Interface for all predictors
SharpBCI.Predictor	An IPredictor which uses a 3-dimensional loci of points in the form of an array of EEGEvent's to classify EEG data Uses nearest neighbor predictions with distance computed by the abstract Compute(double[] x, double[] y) function Predictions occur by computing the distance between the incoming sample and all training samples, pulls the k nearest neighbors, and determines the final prediction
SharpBCI.AggregateKNNCorrelationPredictor
SharpBCI.AggregateKNNDTWPredictor
SharpBCI.IPreprocessor
SharpBCI.CentralizationPreprocessor
SharpBCI.Preprocessors.NonePreprocessor
SharpBCI.Preprocessors.NormalizationPreprocessor
SharpBCI.StandardizationPreprocessor
SharpBCI.IVectorizedSmoother< T >	A common interface for a generic smoother which operates on arrays of type T Currently, only used by FFTPipeable for smoothing
SharpBCI.ExponentialVectorizedSmoother	Implements a vectorized version of exponential smoothing Each value in the input array is assumed to belong to the same time series as the previous value at the same index in the last input array
SharpBCI.XCorrVectorizedSmoother
SharpBCI.OnlineVariance	Simultaneously calculates sample mean and variance in O(1) using Welford-Knuth online algorithm
SharpBCI.Preprocessors
SharpBCI.SerializedConnectionInfo	A class which represents a connection graph for the pipeline
SharpBCI.SerializedPipeline	A class which represents the entire pipeline
SharpBCI.SerializedStage	A class which represents a single stage in the pipeline Can be serialized into a JSON file
SharpBCI.SeriesVariable
SharpBCI.SharpBCI	This is the "main" class which you should create
SharpBCI.SharpBCIBuilder	A builder class for SharpBCIConfig
SharpBCI.SharpBCIConfig	An object which configures a SharpBCI object
SharpBCI.TrainedEvent	A generic event which indicates previously trained event occured