Correcting errors in optical data transmission using neural networks

Optical data communication systems are prone to a variety of processes that modify the transmitted signal, and contribute errors in the determination of 1s from 0s. This is a difficult, and commercially important, problem to solve. Errors must be detected and corrected at high speed, and the classifier must be very accurate; ideally it should also be tunable to the characteristics of individual communication links. We show that simple single layer neural networks may be used to address these problems, and examine how different input representations affect the accuracy of bit error correction. Our results lead us to conclude that a system based on these principles can perform at least as well as an existing non-trainable error correction system, whilst being tunable to suit the individual characteristics of different communication links.

Correcting errors in optical data transmission using neural networks

Optical data communication systems are prone to a variety of processes that modify the transmitted signal, and contribute errors in the determination of 1s from 0s. This is a difficult, and commercially important, problem to solve. Errors must be detected and corrected at high speed, and the classifier must be very accurate; ideally it should also be tunable to the characteristics of individual communication links. We show that simple single layer neural networks may be used to address these problems, and examine how different input representations affect the accuracy of bit error correction. Our results lead us to conclude that a system based on these principles can perform at least as well as an existing non-trainable error correction system, whilst being tunable to suit the individual characteristics of different communication links.

Increasing the electrolyte capacity of alkaline Zn-air fuel cells by scavenging zincate with Ca(OH)2

The use of calcium hydroxide for scavenging zincate species is demonstrated to be a highly effective approach for increasing the electrolyte capacity and improving the performance of the zinc-air fuel cell system. A fundamental approach is established in this study to quantify the formation of calcium zincate as the product of scavenging and the amount of water compensation necessary for optimal performance. The good agreement between predicted and experimental results proves the validity of the proposed theoretical approach. By applying the results of theoretical predictions, both the electrolyte capacity and the cell longevity have been increased by more than 40%. It is also found that, using Ca(OH)2 to scavenge zincate species in concentrated KOH solutions, affects mostly the removal of zincate, rather than ZnO, from the electrolyte, whereas the presence of excess, free, mobile H2O plays a key role in dissolving ZnO and forming zincate. The results obtained in this study demonstrate that the proposed approach can widely and effectively be applied to all zinc-air cell systems during their discharge cycle.