Tham khảo tài liệu 'advances in solid state part 5', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | A Novel Multiclad Single Mode Optical Fibers for Broadband Optical Networks 111 type. Each of two types is divided to two other categories too named type I and II. A small pulse broadening factor small dispersion and dispersion slope as well as small nonlinearity large effective area and low bending loss small mode field diameter are required as the design parameters in Zero dispersion shifted fibers 24 . The performance of a design may be assessed in terms of the quality factor. This dimensionless factor determines the trade-off between mode field diameter which is an indicator of bending loss and effective area which provides a measure of signal distortion owing to nonlinearity 25 . It is also difficult to realize a dispersion shifted fiber while achieving small dispersion slope. Here we attempted to present an optimized MII triple-clad optical fiber to obtain exciting performance in terms of dispersion and its slope 24 . The index refraction profile of the MII fiber structure is shown in Fig. 1. According to the LP approximation 26 to calculate the electrical field distribution there are two regions of operation and the guided modes and propagating wave vectors can be obtained by using two determinants which are constructed by boundary conditions 27 . Fig. 1. Refractive index Profile for MII Structure. For calculation of dispersion and dispersion slope the following parameters are used. p b c 1 Q a c 2 where P and Q are geometrical parameters. Also the optical parameters for the structure are defined as follows. 1 - - K 3 4 For evaluating of the index of refraction difference between core and cladding the following definition is done. A- n - n n - ni 2n4 n4 5 112 Advances in Solid State Circuits Technologies Here we propose a novel methodology to make design procedure systematic. It is done by the aim of optimization technique and based on the Genetic Algorithm. A GA belongs to a class of evolutionary computation techniques 28 based on models of biological .
