In this study, an efficient compression system is introduced, it is based on using wavelet transform and two types of 3Dimension (3D) surface representations (i.e., Cubic Bezier Interpolation (CBI)) and 1 st order polynomial approximation. Each one is applied on different scales of the image; CBI is applied on the wide area of the image in order to prune the image components that show large scale variation, while the 1 st order polynomial is applied on the small area of residue component (i.e., after subtracting the cubic Bezier from the image) in order to prune the local smoothing components and getting better compression gain. Then, the produced cubic Bezier surface is subtracted from the image signal to get the residue component. Then, thebi-orthogonal wavelet transform is applied on the produced Bezier residue component. The resulting transform coefficients are quantized using progressive scalar quantization and the 1 st order polynomial is applied on the quantized LL subband to produce the polynomial surface, then the produced polynomial surface is subtracted from the LL subband to get the residue component (high frequency component). Then, the quantized values are represented using quad tree encoding to prune the sparse blocks, followed by high order shift coding algorithm to handle the remaining statistical redundancy and to attain efficient compression performance. The conducted tests indicated that the introduced system leads to promising compression gain.
The idea of a homomorphism of a cubic set of a KU-semigroup is studied and the concept of the product between two cubic sets is defined. And then, a new cubic bipolar fuzzy set in this structure is discussed, and some important results are achieved. Also, the product of cubic subsets is discussed and some theorems are proved. 2010 AMS Classification: 06F35, 03G25, 08A72.
The aim of this paper is to prove some results for equivalence of moduli of smoothnes in approximation theory , we used a"non uniform" modulus of smoothness and the weighted Ditzian –Totik moduli of smoothness in by spline functions ,several results are obtained .For example , it shown that ,for any the inequality , is satisfied ,finally, similar result for chebyshev partition and weighted Ditzian –Totik moduli of smoothness are also obtained.
The presence of different noise sources and continuous increase in crosstalk in the deep submicrometer technology raised concerns for on-chip communication reliability, leading to the incorporation of crosstalk avoidance techniques in error control coding schemes. This brief proposes joint crosstalk avoidance with adaptive error control scheme to reduce the power consumption by providing appropriate communication resiliency based on runtime noise level. By switching between shielding and duplication as the crosstalk avoidance technique and between hybrid automatic repeat request and forward error correction as the error control policies, three modes of error resiliencies are provided. The results show that, in reduced mode, the scheme achie
... Show MoreTime series analysis is the statistical approach used to analyze a series of data. Time series is the most popular statistical method for forecasting, which is widely used in several statistical and economic applications. The wavelet transform is a powerful mathematical technique that converts an analyzed signal into a time-frequency representation. The wavelet transform method provides signal information in both the time domain and frequency domain. The aims of this study are to propose a wavelet function by derivation of a quotient from two different Fibonacci coefficient polynomials, as well as a comparison between ARIMA and wavelet-ARIMA. The time series data for daily wind speed is used for this study. From the obtained results, the
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
... Show MoreThe aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).
Here, we found an estimation of best approximation of unbounded functions which satisfied weighted Lipschitz condition with respect to convex polynomial by means of weighted Totik-Ditzian modulus of continuity
In this paper, a computational method for solving optimal problem is presented, using indirect method (spectral methodtechnique) which is based on Boubaker polynomial. By this method the state and the adjoint variables are approximated by Boubaker polynomial with unknown coefficients, thus an optimal control problem is transformed to algebraic equations which can be solved easily, and then the numerical value of the performance index is obtained. Also the operational matrices of differentiation and integration have been deduced for the same polynomial to help solving the problems easier. A numerical example was given to show the applicability and efficiency of the method. Some characteristics of this polynomial which can be used for solvin
... Show MoreIn this paper, new transform with fundamental properties are presented. The new transform has many interesting properties and applications which make it rival to other transforms.
Furthermore, we generalize all existing differentiation, integration, and convolution theorems in the existing literature. New results and new shifting theorems are introduced. Finally, comprehensive list of this transforms of functions will be providing.