Optimized BER for channel equalizer using cuckoo search and neural network

The digital data transfer faces issues regarding Inter-Symbol Interference (ISI); therefore, the error rate becomes dependent upon channel estimation and its equalization. This paper focuses on the development of a method for optimizing the channel data to improve ISI by utilizing a swarm intelligence series algorithm termed as Cuckoo Search (CS). The adjusted data through CS is cross-validated using Artificial Neural Network (ANN). The data acceptance rate is considered with 0-10% marginal error which varies in the given range with different bit streams. The performance evaluation of the proposed algorithm using the Average Bit Error Rate (A-BER) and Logarithmic Bit Error Rate (L-BER) had shown an overall improvement of 30-50% when compared with the Kalman filter based algorithm

A preliminary experiment definition for video landmark acquisition and tracking

Six scientific objectives/experiments were derived which consisted of agriculture/forestry/range resources, land use, geology/mineral resources, water resources, marine resources and environmental surveys. Computer calculations were then made of the spectral radiance signature of each of 25 candidate targets as seen by a satellite sensor system. An imaging system capable of recognizing, acquiring and tracking specific generic type surface features was defined. A preliminary experiment definition and design of a video Landmark Acquisition and Tracking system is given. This device will search a 10-mile swath while orbiting the earth, looking for land/water interfaces such as coastlines and rivers

Bio-Inspired, Odor-Based Navigation

The ability of moths to locate a member of the opposite sex, by tracking a wind-borne plume of odor molecules, is an amazing reality. Numerous scenarios exist where having this capability embedded into ground-based or aerial vehicles would be invaluable. The main crux of this thesis investigation is the development of a navigation algorithm which gives a UAV the ability to track a chemical plume to its source. Inspiration from the male moth\u27s, in particular Manduca sexta, ability to successfully track a female\u27s pheromone plume was used in the design of both 2-D and 3-D navigation algorithms. The algorithms were developed to guide autonomous vehicles to the source of a chemical plume. The algorithms were implemented using a variety of fuzzy controllers and ad hoc engineering approaches. The fuzzy controller was developed to estimate the location of a vehicle relative to the plume: coming into the plume, in the plume, exiting the plume, or out of the plume. The 2-D algorithm had a 60% to 90% success rate in reaching the source while certain versions of 3-D algorithm had success rates from 50% to 100%

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

Extending the Finite Domain Solver of GNU Prolog

International audienceThis paper describes three significant extensions for the Finite Domain solver of GNU Prolog. First, the solver now supports negative integers. Second, the solver detects and prevents integer overflows from occurring. Third, the internal representation of sparse domains has been redesigned to overcome its current limitations. The preliminary performance evaluation shows a limited slowdown factor with respect to the initial solver. This factor is widely counterbalanced by the new possibilities and the robustness of the solver. Furthermore these results are preliminary and we propose some directions to limit this overhead

Multiprocessor scheduling with practical constraints

The problem of scheduling tasks onto multiprocessor systems has increasing practical importance as more applications are being addressed with multiprocessor systems. Actual applications and multiprocessor systems have many characteristics which become constraints to the general scheduling problem of minimizing the schedule length. These practical constraints include precedence relations and communication delays between tasks, yet few researchers have considered both these constraints when developing schedulers. This work examines a more general multiprocessor scheduling problem, which includes these practical scheduling constraints, and develops a new scheduling heuristic using a list scheduler with dynamically computed priorities. The dynamic priority heuristic is compared against an optimal scheduler and against other researchers’ approaches for thousands of randomly generated scheduling problems. The dynamic priority heuristic produces schedules with lengths which are 10% to 20% over optimal on the average. The dynamic priority heuristic performs better than other researchers’ approaches for scheduling problems with the practical constraints. We conclude that it is important to consider practical constraints in the design of a scheduler and that a simple heuristic can still achieve good performance in this area