Differential Subordination And Superordination For Analytic And Meromorphic Functions Defined By Linear Operators [QA331. N219 2007 f rb].

Suatu fungsi f yang tertakrif pada cakera unit terbuka U dalam satah kompleks C disebut univalen jika fungsi tersebut memetakan titik berlainan dalam U ke titik berlainan dalam C. A function f defined on the open unit disk U of the complex plane C is univalent if it maps different points of U to different points of C

On certain class of analytic . . .

Motivated by a multiplier transformation and some subclasses of meromorphic functions which were defined by means of the Hadamard product of the Cho-Kwon-Srivastava operator, we define here a similar transformation by means of the Ghanim and Darus operator. A class related to this transformation will be introduced and the properties will be discussed

Geometrical Theory of Analytic Functions

The book contains papers published in the Mathematics Special Issue, entitled "Geometrical Theory of Analytic Functions". Fifteen papers devoted to the study concerning complex-valued functions of one variable present new outcomes related to special classes of univalent functions, differential equations in view of geometric function theory, quantum calculus and its applications in geometric function theory, operators and special functions associated with differential subordination and superordination theories and starlikeness, and convexity criteria

ORTHOGONAL WAVELET FUNCTION FOR COMPRESSION SATELLITE IMAGERY OF PEAT FOREST FIRES

Background: In the process of digital image data representation, constrained the number of data volumes are required. One of the main sources of information in data processing of imagery is satellite imagery. Some applications of remote sensing technology requires a good quality image but in small size. Purpose: This study focuses on image compression is done to reduce the size of the image needs. However, the information contained in the image retained its existence. Method: In this study, using 17 orthogonal wavelet function used to reduce data satellite images of peat forest fires. Then, 17 of these orthogonal wavelet functions are compared with the parameter measurement i.e. PSNR (Peak Signal to Noise Ratio) and compression ratio. The benchmark of image compression is seen from the largest PSNR and large compression ratio Finding: Based on orthogonal wavelet function testing, then the Haar (daubechies 1) wavelet function results obtained has the highest PSNR for all level of decomposition on all test image i.e 50.783 dB for test image 1, 50.954 dB for image 2 and 49.855 dB for image 3. For the highest compression ratio on all test image is a function of wavelet symlet 8 i.e 97.00% for image 1, 97.05% for image 2 and 96.90% for image 3. Originality value: Satellite imagery that has been reduced would contribute to facilitating the processing of data as well as data input for the creation of digital image processing for system detection peat forest fires hotspots