The aim of this paper is to study the best approximation of unbounded functions in the
weighted spaces
,
1, 0 ,
p
p L α
α ≥>.
Key Words: Weighted space, unbounded functions, monotone approximation
This study aimed to identify the degree of frustration and guilt among addicts who hurt themselves with drug, and to know the addicts perspective who are in treatment clinics and rehabilitation centers in Palestine, in order to achieve this goal aDeterminationThe study population has been identified , this study population consisted of ' (82) addict, the researcher used the descriptive analytical method which is appropriate for this study, so the researcher questioned the addicts who are in treatment clinics and rehabilitation centers in Palestine and analyze their responses in light of some of the variables.
The study results showed that drug addicts who ar
... Show MoreThe design of the interior spaces process the product of intellectual civilization expresses the prevailing thought, discoverers of principles and beliefs through the sheen reflects the present, and generating languages graphical variety caused a different revolution in design mounting structure, and because of the complex nature of the interior spaces were and we have to be a reflection of cultural reality of being a form of cultural expression and true embodiment of scientific developments prevailing for each stage where she was born, the changes occurring in human thought and then extremism and the discrepancy tastes among individuals all communities factors have caused a change in the design structure involving modernization an
... Show MoreIn this paper, the definition of fuzzy anti-inner product in a linear space is introduced. Some results of fuzzy anti-inner product spaces are given, such as the relation between fuzzy inner product space and fuzzy anti-inner product. The notion of minimizing vector is introduced in fuzzy anti-inner product settings.
A complete metric space is a well-known concept. Kreyszig shows that every non-complete metric space can be developed into a complete metric space , referred to as completion of .
We use the b-Cauchy sequence to form which “is the set of all b-Cauchy sequences equivalence classes”. After that, we prove to be a 2-normed space. Then, we construct an isometric by defining the function from to ; thus and are isometric, where is the subset of composed of the equivalence classes that contains constant b-Cauchy sequences. Finally, we prove that is dense in , is complete and the uniqueness of is up to isometrics
In this paper, we provide some types of - -spaces, namely, - ( )- (respectively, - ( )- , - ( )- and - ( )-) spaces for minimal structure spaces which are denoted by ( -spaces). Some properties and examples are given.
The relationships between a number of types of - -spaces and the other existing types of weaker and stronger forms of -spaces are investigated. Finally, new types of open (respectively, closed) functions of -spaces are introduced and some of their properties are studied.
This paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin
... 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]).