Signal & Image Processing Subroutine Libraries for OS/2 Platforms

A comprehensive range of signal and image processing subroutine libraries for Intel architecture IBM PC compatibles running IBM's OS/2 operating system - from laptop clients to large multiprocessor servers.

Our extensive collection includes not only the standard correlations, convolutions, filters, and fast transforms (Fourier, Hilbert, Hartley, etc.) found in many stand alone products, but also advanced parametric spectral estimation, low noise state space filters, beamformers, and low sidelobe optimal windowing.  Most algortihms are available in multidimensional versions.  Our proven codes are  TESTED and OPTIMIZED  to your specific processor and application. Target processors include  embedded 80x86/80x87's and 80486's to  multiprocessor Celeron and Pentium architectures.  A number of routines are available for popular DSP plug-in boards, including legacy ones such as the National Instruments AT-DSP2200 series, AT&T WE DSP32C, and Motorola 96000 series.

Individual routines and libraries can be supplied as dynamic link libraries (dll), static libraries (lib), or object files (obj). We also have the capability to supply dynamic loadable drivers (dld), virtual device drivers (vdd), and physical device drivers (pdd) should they be required.

Calling languages are typically FORTRAN, C++, and C. Other languages such as Ada, REXX, and G can often be accommodated.

When you want to get your new application up and running quickly, or you wish to extend the scope or increase the speed of an existing application, call on MAI to save you time and money!

MAI had been an IBM Premier Level Solutions Developer

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Popular Signal & Image Processing Routines/Functions

Windowing of all kinds, including multidimensional

Filtering
- IIR, all kinds, sometimes multidimensional
- FIR, all kinds, usually multidimensional

Fast Transforms, including multidimensional

Classical Spectral Estimation

Autoregressive Spectral Estimation
- Block Data Algorithms
- Sequential Data Algorithms
- Moving Average (ARMA)

Prony's Method

Minimum Varience Spectral Estimation

Eigenanalysis  Frequency Estimation

Multichannel Spectral Estimation
- Classical
- ARMA
- AR
- MA
- Yule-Walker
- Levinson
- Block-Toeplitz
- Autoregressive

Beamforming
- Weighted Delay and Sum
- Filter and Sum
- Frequency Domain
- Interpolation
- Narrowband
- High Resolution
- Inverse

Signal Restoration

Wavenumber-Frequency Filtering

Normal Moveout Correction

Random and Pseudo Random Noise Generation