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* CONSTRAINTS * This module does not handle data which is considered out of range by the * application(i.e. fixed constants which represent error condition) * * Maximum weight value must be limited to 128 to prevent an overflow * condition during the calculation. * * The internal data type mu ...

Knowledge of the process noise covariance matrix is essential for the application of Kalman filtering. However, it is usually a difficult task to obtain an explicit expression of for large time varying systems. This paper looks at an adaptive Kalman filter method for dynamic harmonic state estimatio ...

This code was used for making the practical measurements in section 2.3 of my thesis. This Matlab code allows an OFDM signal to be generated based on an input data file. The data can be random data, a grey scale image, a wave file, or any type of file. The generated OFDM signal is stored as a window ...

要用到开发工具SD-H08，是free scale 的应用程序

Pre-designed and pre-verified hardware and software blocks can be combined on chips for many different applicationsVthey promise large productivity gains.

real property management,information management system developed by VB, using very conveniently.good real property management has such large information

In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discrete-data linear filtering problem. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area o ...

In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in ...

In this report we provide an overview of several closely related methods developed during the last few yers, to smooth, denoise, edit, compress, transmit, and animate very large polygonal models.

This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic method of increasing the height-to-width ratio of the cluster histogram, we develop a novel algorithm – CLOPE, which is v ...