Carrier Synchronization in High Bit-Rate Optical Transmission Systems

In this dissertation, design of optical transmission systems with differential detection and coherent detection is briefly described. More over, algorithms for carrier synchronization and phase estimation with their implementation in high bit-rate optical transmission systems are proposed

Optical Communication with Semiconductor Laser Diode

Theoretical and experimental performance limits of a free-space direct detection optical communication system were studied using a semiconductor laser diode as the optical transmitter and a silicon avalanche photodiode (APD) as the receiver photodetector. Optical systems using these components are under consideration as replacements for microwave satellite communication links. Optical pulse position modulation (PPM) was chosen as the signal format. An experimental system was constructed that used an aluminum gallium arsenide semiconductor laser diode as the transmitter and a silicon avalanche photodiode photodetector. The system used Q=4 PPM signaling at a source data rate of 25 megabits per second. The PPM signal format requires regeneration of PPM slot clock and word clock waveforms in the receiver. A nearly exact computational procedure was developed to compute receiver bit error rate without using the Gaussion approximation. A transition detector slot clock recovery system using a phase lock loop was developed and implemented. A novel word clock recovery system was also developed. It was found that the results of the nearly exact computational procedure agreed well with actual measurements of receiver performance. The receiver sensitivity achieved was the closest to the quantum limit yet reported for an optical communication system of this type

Orthogonal multicarrier modulation for high-rates mobile and wireless communications

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN037085 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Publications of the Jet Propulsion Laboratory - July through December 1970

Bibliography of technical literature resulting from aerospace research and development at Jet Propulsion Laboratorie

The deep space network, volume 2 Progress report, Jan. - Feb. 1971

Deep Space Network, Ground Communications Facility, Space Flight Operations Facility, and Deep Space Instrumentation Facility research and development - Vol.

18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I Table of Contents ........................ Page III Symposium Committees .............. Page IV Special Thanks ............................. Page V Conference program (incl. page numbers of papers) ................... Page VI Conference papers Invited talks ................................ Page 1 Regular Papers ........................... Page 14 Wednesday, May 26th, 2010 ......... Page 15 Thursday, May 27th, 2010 .......... Page 110 Friday, May 28th, 2010 ............... Page 210 Author index ............................... Page XII

Space Programs Summary No. 37-36

Research in systems, guidance and control, space sciences, engineering, telecommunications and propulsion for space exploration program

Three dimensional nanowire networks for reservoir computing.

Over the past few decades, machine learning has become integral to our daily lives. Deep learning has revolutionized industry and scientific research, enabling us to solve complex problems that were previously intractable. Similarly, as computer components have become smaller and more efficient, humanity has gained unprecedented access to affordable hardware. However, the looming fundamental limits on transistor sizes have sparked widescale investigation into alternative means of computation that can circumvent the restrictions imposed by conventional computer architecture. One such method, called reservoir computing, maps sequential data onto a higher dimensional space by using deep neural networks or nonlinear dynamical systems found in nature. Networks of nanowires are currently under consideration for a wide range of electronic and optoelectronic applications, and have recently been pursued as potential devices for reservoir computing. Nanowire devices are usually made by sequential deposition, which inevitably leads to the stacking of wires on top of one another. This thesis builds a fully three dimensional simulation of a nanowire network and demonstrates the effect of stacking on the topology of the resulting networks. Perfectly 2D networks are compared with quasi-3D networks, and both are compared to the corresponding Watts Strogatz networks, which are standard benchmark systems. By investigating quantities such as clustering, path length, modularity, and small-world propensity it is shown that the connectivity of the quasi-3D networks is significantly different to that of the 2D networks. This thesis also explores the effects of stacking on the performance in two reservoir computing tasks: memory capacity and nonlinear transformation. After developing a dynamical model that describes the connections between individual nanowires, a comparison of reservoir computing performance is made between 2D and quasi-3D networks. Most previous simulations use the signals from every wire in the network. In this thesis an electrode configuration is used that is a more physically realistic representation of nanowire networks. The result is that the two different network types have a strikingly similar performance in reservoir computing tasks, which is surprising given their radically different topologies. However, there also exist key differences: for large numbers of wires the upper limit on the performance of the 3D networks is significantly higher than in the 2D networks. In addition, the 3D networks appear to be more resilient to changes in the input parameters, generalizing better to noisy training data. Since previous literature suggests that topology plays an important role in computing performance, these results may have important implications for future applications of nanowire networks