This paper presents algorithms that allow the realization of multi-valued functions as a multi-level network consisting of minand max-gates. The algorithms are based on bi-decomposition of function intervals, a generalization of incompletely specified functions. Multi-valued derivation operators are applied to compute decomposition structures. For validation the algorithms have been implemented...

| This paper introduces a new decomposition method for Boolean functions. It is based on generalized dominators, which provide eecient means to generate both conjunctive divisors and disjunctive \deductors". Concise factored form representation of a Boolean function can be obtained by performing BDD decomposition iteratively. The choice of the decomposition type depends on the cost of the gener...

Accuracy of inertial navigation system (INS) is limited by inertial sensors imperfections. Before using inertial sensors signals in the data fusion algorithm, noise removal method should be performed, in which, wavelet decomposition method is used. In this method the raw data is decomposed into high and low frequency data sets. In this study, wavelet multi-level resolution analysis (WMRA) techn...

The real world signals do not exist without noise. Wavelet Transform based denoising is a powerful method for suppressing noise in signals. In this paper, signal denoising based on Double-Density Discrete Wavelet Transform (DDDWT) and Dual-Tree Discrete Wavelet Transform (DTDWT) methods are implemented with optimum values of threshold point and level of decomposition. Based on the intensity of ...

Most image coding systems rely on signal processing concepts such as transforms, VQ, and motion compensation. In order to achieve significantly lower bit rates, it will be necessary to devise encoding schemes that involve mid-level and high-level computer vision. Model-based systems have been described, but these are usually restricted to some special class of images such as head-and-shoulders ...