Gaussian beam intensity follows a normal distribution curve in free space. As it propagates, the divergence and the width increase with distance. Using paraxial approximation, the effect of the distance on the intensity, width, radius of curvature and divergence was investigated. Matlab software was used for characteristics parameters calculation. The divergence angle range (26.67 4mm, and compared with the divergence angle range (43 for the distance between 3mm and 4.5mm. The result obtained in this work indicates smaller angles of divergence that can produce a better beam quality and intensity. Finally, this will serve as a great importance for application such as pointing, free space optical communication etc. Keyword: Gaussian beam, Paraxial approximation, Beam divergence, Normal distributio curve.Recently, free-space optical (FSO) systems are competitively being installed as broad band access communication links. Depending on the application, a laser beam with a different shape may have favorable characteristics over a , November, 2018Gaussian beam intensity follows a normal distribution curve in free space . As it propagates, the divergence and the width increase with distance. Using paraxial approximation, the distance on the intensity, width, radius of curvature and divergence was investigated. Matlab software was used for characteristics parameters calculation. The divergence angle range (26.67 0 35.85 0 ) was obtained at a distance between 3mm and 4mm, and compared with the divergence angle range (43 0 53 0 ) obtained experimentally for the distance between 3mm and 4.5mm. The result obtained in this work indicates smaller hat can produce a better beam quality and intensity. Finally, this will serve as a great importance for application such as pointing, free space optical

This paper describes the Lagrange based formulation of bit frames over number of pictures in a group for motion compensated video compression. Theoretical insight on bit assignment is accomplished by applying Lagrange multip cost function for a real-time computational analysis. Video signals are compressed at optimal bit allocation for qualitative reconstruction at the decoder (receiver) depending upon the number of hypothesis used in coding the signal. This has m compensation (MHMC) a great process in the prediction of the actual signal through the combination of more than one motion compensated prediction (MCP). Optimal Bits were allocated to multi-hypothesis frames using MATLAB to opti frames per group of pictures (GOP) decoded for an improved signal compression. Simulation results show that an optimal bit assignment of the range 0.089 bpp to 0.159 bpp was realized with eight numbers of hypotheses frames per hypotheses actualizes optimal bit assignment for motion compensation. This shows a qualitative signal compression performance analysis for high technology motion pictures in communication services and storage pro greater time correlation between hypotheses and helps in the improvement of coding and reconstruction quality of video signals.