Since their introduction in the 1960s, cochlear implants （CIS） have undergone several transformations, ulti- mately positioning themselves as the best-performing neural prosthesis available today. They have also bee...Since their introduction in the 1960s, cochlear implants （CIS） have undergone several transformations, ulti- mately positioning themselves as the best-performing neural prosthesis available today. They have also been recognized as a unique tool for studying the potential protective effects of patterned electrical stimulation on the developing auditory system, with results from animal models often changing the manner in which CIs are used clinically to deliver auditory information to the brain （Moore and Shannon, 2009）. From the development of the first successful commercial single-channel device, they have evolved into multi-channel devices that are part of the national health programmes of several coun- tries. From the limited speech information provided by the early, rudimentary cochlear implants, these devices are now in a position to deliver intelligible speech infor- mation to the auditory system, largely due to advances in signal processing. Concerted efforts from several dis- ciplines, including engineering, acoustics, neurobiology and otolaryngology have ensured that the continued development of CI technology has resulted in signifi- cant benefits to individuals with profound sensorineural hearing loss.展开更多
The roll motions of ships advancing in heavy seas have severe impacts on the safety of crews,vessels,and cargoes;thus,it must be damped.This study presents the design of a rudder roll damping autopilot by utilizing th...The roll motions of ships advancing in heavy seas have severe impacts on the safety of crews,vessels,and cargoes;thus,it must be damped.This study presents the design of a rudder roll damping autopilot by utilizing the dual extended Kalman filter(DEKF)trained radial basis function neural networks(RBFNN)for the surface vessels.The autopilot system constitutes the roll reduction controller and the yaw motion controller implemented in parallel.After analyzing the advantages of the DEKF-trained RBFNN control method theoretically,the ship’s nonlinear model with environmental disturbances was employed to verify the performance of the proposed stabilization system.Different sailing scenarios were conducted to investigate the motion responses of the ship in waves.The results demonstrate that the DEKF RBFNN based control system is efficient and practical in reducing roll motions and following the path for the ship sailing in waves only through rudder actions.展开更多
基金funded in part by the Rhodes Trust,United Kingdom(AI)and the Wellcome Trust,United Kingdom(DEHH)
文摘Since their introduction in the 1960s, cochlear implants （CIS） have undergone several transformations, ulti- mately positioning themselves as the best-performing neural prosthesis available today. They have also been recognized as a unique tool for studying the potential protective effects of patterned electrical stimulation on the developing auditory system, with results from animal models often changing the manner in which CIs are used clinically to deliver auditory information to the brain （Moore and Shannon, 2009）. From the development of the first successful commercial single-channel device, they have evolved into multi-channel devices that are part of the national health programmes of several coun- tries. From the limited speech information provided by the early, rudimentary cochlear implants, these devices are now in a position to deliver intelligible speech infor- mation to the auditory system, largely due to advances in signal processing. Concerted efforts from several dis- ciplines, including engineering, acoustics, neurobiology and otolaryngology have ensured that the continued development of CI technology has resulted in signifi- cant benefits to individuals with profound sensorineural hearing loss.
基金a part of the project titled ’Intelligent Control for Surface Vessels Based on Kalman Filter Variants Trained Radial Basis Function Neural Networks’ partially funded by the Institutional Grants Scheme(TGRS 060515)of Tasmania,Australia
文摘The roll motions of ships advancing in heavy seas have severe impacts on the safety of crews,vessels,and cargoes;thus,it must be damped.This study presents the design of a rudder roll damping autopilot by utilizing the dual extended Kalman filter(DEKF)trained radial basis function neural networks(RBFNN)for the surface vessels.The autopilot system constitutes the roll reduction controller and the yaw motion controller implemented in parallel.After analyzing the advantages of the DEKF-trained RBFNN control method theoretically,the ship’s nonlinear model with environmental disturbances was employed to verify the performance of the proposed stabilization system.Different sailing scenarios were conducted to investigate the motion responses of the ship in waves.The results demonstrate that the DEKF RBFNN based control system is efficient and practical in reducing roll motions and following the path for the ship sailing in waves only through rudder actions.
