What Is Dataplore ®?

Dataplore ® is a software tool designed for the analysis of signals and time series data of any kind, in particular for scientific, economic and engineering purposes.

The guidelines for the design of Dataplore ® were:

• Easy-to-use graphical user interface.
• High level of integration of a wide variety of signal processing functions in a common interface.
• State-of-the-art functionality for modern systems analysis.
• Support of all standard hardware and software platforms.

Beside standard options (like file I/O, printing capabilities etc.) Dataplore ® covers the following features:

• Client-server and batch mode operation
• Multi-threading and job control
• Extensibility of the signal processing functionality and solution of user-specific problems through macro programming
• Histogram plots, 2D and 3D delay plots, and phase plots
• Time-frequency spectra, isoline plots, and 3D grid plots
• Computation of signal statistics (mean, standard deviation, skewness, kurtosis, modes, median, linear regression coefficients etc.), central moments and various statistical tests
• Signal manipulation (subsampling, DC removal, linear compensation)
• Generation of surrogate data and noise (fractal, Gaussian, Poisson etc.) signals
• Statistical tests (test for non-white-noise, non-normal-distributed data, the mean of a Gaussian, the variance of a Gaussian, different means, different variances, different histograms; Kolmogorov-Smirnov test, Wilcoxon test and BDS test)
• Regression methods (Box-Cox transform; R/S statistics; long term correlation analysis; detrended fluctuation analysis; linear, exponential, power and multilinear regression; principal component analysis)
• Parametric modelling (ARMA, ARIMA, ARMAX, ARIMAX and NARMA modeling; ARMA model order estimation; ARMA spectral density)
• Spectral analysis and Fourier transform (amplitude, power and phase spectrum with optional windowing, cross spectrum, chirp-z transform, real and complex cepstrum, coherence etc.)
• Adaptive filters and estimators (momentary mean, power, bandpower, frequency)
• Linear filters (FIR filters, IIR filters, frequency domain filters)
• Wavelet transforms (decomposition and reconstruction with orthogonal and biorthogonal wavelets, approximation and detail calculation, wavelet packet decomposition, continuous wavelet transform)
• Methods of nonlinear dynamics (recurrence plots, peak-to-peak intervals, false nearest neighbors, correlation integral and dimension, pointwise correlation integral, global and local Lyapunov exponents)
• Tools for coupling analysis of complex systems (global and local transinformation of two time series, post event scan, synchronicity histogram, mutual cross information, conditional coupling convergence (PCCD), delta test, post event time histogram, ARMA dependece)
• Advanced noise reduction methods
  • wavelet soft, hard and sure shrinking techniques
  • nonlinear noise reduction methods
• Arithmetic operations (adding of constants, pointwise sum and product of signals, rescaling, reciprocal) and mathematical standard functions (logarithm, exponential function, trigonometric functions, error function, etc.)
• Generation of various noise signals (Gaussian, grey, uniform, Poisson and fractal noise) and simulation of ARMA processes
• Analytical operations (time derivative, integration, autocorrelation, cross correlation, instantaneous analytical phase)
• All standard options (like file I/O, printing capabilities etc.)
• Support of various file formats (Dataplore binary and ASCII formats, MegaWave, WAVE audio files, ASCII raw data)
• Signal handling (mouse supported clipping, editing of signal properties, ...)