NI Releases LabVIEW Advanced Signal Processing Toolkit

Toolkit simplifies time-series analysis, time-frequency analysis, and wavelet applications.

Toolkit simplifies time-series analysis, time-frequency analysis, and wavelet applications.

By DE Editors

Toolkit simplifies time-series analysis, time-frequency analysis, and wavelet applications.



National Instruments (Austin, TX) announced the release of NI LabVIEW Advanced Signal Processing Toolkit Version 7.5, a suite of easy-to-use, palette-based tools, example programs, and utilities that extends the LabVIEW graphical development environment with measurement-oriented signal processing and analysis. Engineers and scientists now can access new graphical tools for simplifying work that incorporates time-series analysis, time-frequency analysis and wavelets. In addition, professors can use the toolkit’s interactive, graphical methodology to effectively illustrate these key signal processing concepts to engineering students.

 The LabVIEW Advanced Signal Processing Toolkit includes new features for making advanced analysis easier to apply and learn. Express VIs (configuration-based functions) can be used to interactively specify signal processing parameters and review immediate results. The toolkit also delivers a new time-series analysis component for tasks such as model-based spectral analysis, which can be used for high-resolution spectral analysis on small data sets. For analysis such as data mining and feature extraction in applications including biomedical, mechanical, and seismological signals, engineers and scientists can use the independent component analysis and principal component analysis tools as part of the new time-series analysis functionality.

Alternative approaches require engineers and scientists to develop their applications in non-intuitive, text-based programming languages and integrate several vendors’ products to analyze live signal sources. With the LabVIEW Advanced Signal Processing Toolkit, they can access new features for simplifying these common measurement-oriented tasks with a single software tool. For instance, online Gabor transform and expansion routines included in the toolkit work with streaming data sources to help engineers and scientists acquire and immediately analyze live data. The toolkit also features high-level tools for wavelet applications such as PDF estimation and signal denoising. Wavelets have proven useful for signal and image processing for peak, edge, and ridge detection.

The LabVIEW Advanced Signal Processing Toolkit also includes the LabVIEW Digital Filter Design Toolkit 7.5, which provides tools for design, validation and implementation of software-based digital filters with LabVIEW FPGA and C code generation capabilities for chip-level implementation. Design and test engineers can use this toolkit, which is also available separately, to ensure a seamless digital filter design process from conception to completion while reducing development costs.

For more information, visit ni.com/analysis

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