Bilinear s-z with frequency transformation using Pascal matrix operation

2006 ◽  
Author(s):  
S. Chivapreecha ◽  
S. Sriyapong ◽  
S. Junnapiya ◽  
K. Dejhan
Keyword(s):  
Matrix Operation ◽  
Frequency Transformation ◽  
Pascal Matrix

Design of Dual-band Cavity Filter Using Frequency Transformation Method

2012 ◽  
Vol 34 (6) ◽  
pp. 1489-1493
Author(s):  
Xin Kou ◽  
Zhong-yin Xiao ◽  
Chun-yan Huang ◽  
Hao Li ◽  
Jun-jun Chu
Keyword(s):  
Transformation Method ◽  
Dual Band ◽  
Frequency Transformation

scholarly journals Some Properties of the(p,q)-Fibonacci and(p,q)-Lucas Polynomials

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
GwangYeon Lee ◽  
Mustafa Asci
Keyword(s):  
Generating Functions ◽  
Combinatorial Identities ◽  
Fibonacci Polynomials ◽  
Lucas Polynomials ◽  
Pascal Matrix ◽  
Riordan Arrays ◽  
Combinatorial Sums

Riordan arrays are useful for solving the combinatorial sums by the help of generating functions. Many theorems can be easily proved by Riordan arrays. In this paper we consider the Pascal matrix and define a new generalization of Fibonacci polynomials called(p,q)-Fibonacci polynomials. We obtain combinatorial identities and by using Riordan method we get factorizations of Pascal matrix involving(p,q)-Fibonacci polynomials.

Wavelet Frequency Transformation for Specific Weeds Recognition

2021 ◽  
Author(s):  
Shaban Habib ◽  
Ishrat Khan ◽  
Muhammad Islam ◽  
Waleed Albattah ◽  
Saleh Mohammed Alyahya ◽  
...  
Keyword(s):  
Frequency Transformation

CPU AND GPU PERFORMANCE ANALYSIS ON 2D MATRIX OPERATION

2021 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Kwek Benny Kurniawan ◽  
YB Dwi Setianto
Keyword(s):  
Graphic Processing Unit ◽  
Computing Time ◽  
General Purpose ◽  
Parallel Processors ◽  
Processing Unit ◽  
Matrix Operation ◽  
Industry Standard ◽  
Programming Interfaces ◽  
Complete Matrix ◽  
Matrix Calculation

GPU or Graphic Processing Unit can be used on many platforms in general GPUs are used for rendering graphics but now GPUs are general purpose parallel processors with support for easily accessible programming interfaces and industry standard languages such as C, Python and Fortran. In this study, the authors will compare CPU and GPU for completing some matrix calculation. To compare between CPU and GPU, the authors have done some testing to observe the use of Processing Unit, memory and computing time to complete matrix calculations by changing matrix sizes and dimensions. The results of tests that have been done shows asynchronous GPU is faster than sequential. Furthermore, thread for GPU needs to be adjusted to achieve efficiency in GPU load.

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