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A standard receiver autonomous integrity monitoring (RAIM) technique for the global positioning system (GPS) has been dedicated to provide an integrity monitoring capability for safety-critical GPS applications, such as in civil aviation for the en-route (ER) through non-precision approach (NPA) or lateral navigation (LNAV). The performance of the existing RAIM method, however, may not meet more stringent aviation requirements for availability and integrity during the precision approach and landing phases of flight due to insufficient observables and/or untimely warning to the user beyond a specified time-to-alert in the event of a significant GPS failure. This has led to an enhanced RAIM architecture ensuring stricter integrity requirement by greatly decreasing the detection time when a satellite failure or a measurement error has occurred. We thus attempted to devise a user integrity monitor which is capable of identifying the GPS failure more rapidly than a standard RAIM scheme by incorporating the RAIM with the relative entropy, which is a likelihood ratio approach to assess the inconsistence between two data streams, quite different from a Euclidean distance. In addition, the delay-coordinate embedding technique needs to be considered and preprocessed to associate the discriminant measure obtained from the RAIM with the relative entropy in the new RAIM design. In simulation results, we demonstrate that the proposed user integrity monitor outperforms the standard RAIM with a higher level of detection rate of anomalies which could be hazardous to the users in the approach or landing phase and is a very promising alternative for the detection of deviations in GPS signal. The comparison also shows that it enables to catch even small anomalous gradients more rapidly than a typical user integrity monitor. [ABSTRACT FROM AUTHOR]

Abstract: Wireless Brain Machine Interface (BMI) communication protocols are faced with the challenge of transmitting the activity of hundreds of neurons which requires large bandwidth. Previously a data compression scheme for neural activity was introduced based on Self Organizing Maps (SOM). In this paper we propose a dynamic learning rule for improved training of the SOM on signals with sparse events which allows for more representative prototype vectors to be found, and consequently better signal reconstruction. This work was developed with BMI applications in mind and therefore our examples are geared towards this type of signals. The simulation results show that the proposed strategy outperforms conventional vector quantization methods for spike reconstruction. [Copyright &y& Elsevier]

Abstract: A wireless type of chip-to-chip communication (WCC) technology is proposed as the next generation of 3D semiconductor technology. To demonstrate the feasibility of this technology, we designed a coil, transmitter and receiver for wireless chip-to-chip communication using a 50-nm digital CMOS process. The coil is designed using inductive coupling with design parameters that include the number of turns, the metal width, and the space between adjacent metal lines. A differential transceiver structure is proposed for the WCC technology. The transmitter of the transceiver acts as a termination and bias circuit for the receiver while the transceiver is operating as a receiver. The receiver is designed with a typical differential amplifier and a latch to recover the transmitted original digital signal. The proposed transceiver and coil for the proposed WCC technology is implemented using commercial 50-nm digital CMOS technology. Experimental results successfully demonstrate the feasibility of the WCC technology. [Copyright &y& Elsevier]