ActiveX Software for Visual Basic 6/.NET, C++ 6/.NET, Delphi, Borland C++ Builder: Matrix Maths, Time Series
 
 Home   |   Products   |   Testimonials   |   Prices   |   Support   |   Contact   |   Publications   |   About   |   Buy Now
Quick Links   Home   Purchase   Support
Products   Product Home   ActiveX/COM Components   .NET Components   Version History
Support   Support Home   Installation Help
About Us   Company Info   Clients   Testimonials   Publications   Contact Us

   Signal Processing Software - Spectral Analysis ActiveX DLL
 

    LinearPrediction/X 5.0
Signal Processing ActiveX Control and COM Object

Product Features  Download  Product FAQ  Screen Shots!   Prices Buy Now

Do you need to analyze time series data? Need to quickly determine an auto-regressive linear predictor from a data set? Linear Prediction/X lets you quickly and easily implement a range of signal processing algorithms that let you do just that.

With full source samples in Visual Basic 6, Visual Basic.Net, you can quickly produce solutions to analyze time series data. Use Linear Prediction/X in your VB, Excel/VBA, Visual C++ or Borland C++ Builder applications to model time series data or perform system identification using FIR (Finite Impulse Response), IIR (Infinite Impulse Response), AR (Autoregressive), ARX (Autoregressive Exogenous Input), or MA (Moving Average) models.

Linear Prediction/X ActiveX and COM Control

The LinearPrediction/X Signal Processing Control implements a number of well known linear prediction algorithms.

Algorithms for autoregressive model estimation, time domain filtering, and random noise generation are included.

A range of well known algorithms are implemented, such as the Yule-Walker, Burg and Levinson algorithms for processing block data.

For online model estimation of FIR and IIR systems, the LMS (Least mean Square) and Kalman algorithms are supplied.

 

Screen shot of an application built using Linear Prediction/X.

Linear Prediction/X Features

Methods are provided to determine the stability of a model, as well as determine the poles, zeros, and the frequency response of a model. The following methods are included:

Yule-Walker
Burg (Maximum Entropy Method for Spectral Analysis)
Levinson
Backward Levinson
Frequency Response of model
Schur-Cohn
SignalNoiseRatio
Pole, Zeros from Polynomials (Root Finding)
Polynomial model from Poles/Zeros
Filter, ProcessData, ARProcess
Train: LMS (Least Mean Square), Kalman Filter adaptive learning algorithms
Predict
Noise
StabilityTest
CreateModel, GetModelSize, Clear, Delete
Load, Save
LoadData, SaveData
SetWeights, GetWeights, SetARWeights, GetARWeights, SetMAWeights, GetMAWeights
LoadWeights, SaveWeights

Linear Prediction/X provides a range of simple functions to create, delete, load, save and train or parametrize linear models. The sample application included shows how to use linear models in a range of areas. The trial version of Linear Prediction/X is feature limited to up to order 8 models, and 2000 data points. However it is possible to develop and even compile trial applications. By purchasing Linear Prediction/X you obtain full functionality.

Linear Prediction/X Implementation

Linear Prediction/X is a single tiny DLL, only around 300k in size! It is written in efficient C/C++ so your application will benefit. Because it is an ActiveX and COM component it provides powerful algorithms in a single DLL that can be used in wide range of Windows applications. It requires no user interface and can be accessed by any ActiveX compatible development environment, including VB, Excel, VBA and VC++.

Linear Prediction/X supports threaded blocking and non-blocking modes. This means for lengthy computations, you can use the control in a program, pass it some data for processing and the program can then run other tasks and respond to user input while the computations are taking place. When processing is complete, an event is fired and the program continues from the data processing step. This blocking/non-blocking mode is under program control. Error codes are returned from the event indicating the success or otherwise of the data processing. The computations can also be interrupted under program control by the user, for example, it is straight forward to implement a "Stop" button to direct the computations to be stopped.

Matrix data used with Linear Prediction/X and returned from the control can have different index starting values in Visual Basic. For example, you can choose to index your data from 0 or 1. Linear Prediction/X will pass the data back in an array indexed from the value you specify in a property of the control. All data used and returned with Linear Prediction/X is in double format. This means it is suitable for use with Visual Basic and Visual C++. In addition, all our controls are designed to function together, so you can build your applications quickly and easily.