emmorts / SignalSharp

SignalSharp is a library designed for signal processing and time series analysis.

SignalSharp

C# library designed for efficient signal processing and time series analysis.

Algorithms

Change Point Detection

• PELT: Pruned Exact Linear Time method detects multiple change points with high efficiency, using a pruning technique to improve computation speed without sacrificing accuracy.
• CUSUM: Detects shifts in the mean value of a signal by accumulating deviations from a target value over time.

Cost Functions

• L1 Cost Function: Robust against outliers and non-Gaussian noise.
• L2 Cost Function: Ideal for normally distributed data.
• RBF Cost Function: Handles non-linear relationships between data points.

Smoothing and Filtering

• Savitzky-Golay Filter: Smooths data to reduce noise while preserving the shape of the signal.
• Moving Average: Smoothing a signal using a moving average filter.
• Kalman Filter: Estimates the state of a linear dynamic system from a series of noisy measurements.

Resampling

• Downsampling: Reducing the number of samples in a signal.
• Segment Statistics: Computing statistics (mean, median, max, min) for segments of a signal.

Installation

To install SignalSharp, you can use NuGet Package Manager:

dotnet add package SignalSharp

Usage

Refer to documentation for examples and API documentation.

Contributing

Contributions are welcome! If you have ideas, suggestions, or bug reports, feel free to open an issue or submit a pull request.