303 research outputs found

    A local bus for MCM-based microinstrumentation systems

    Get PDF
    A local bus is described which is designed for use in a multi-chipcomposed microinstrumentation system. The bus is able to transmit a digital code, bitstream, analog voltage, frequency, duty-cycle and also provides calibration facilities, service request and interrupt request for the smart sensors. Corresponding sensor bus interface was implemented in a 1.6 m CMOS process and successfully tested in a local sensor network.Junta Nacional de Investigação Científica e Tecnológica - Praxis XXI-BD/5181/95. STW - Project DEL 55.3733. TUDelft

    A local bus for multi-chip-module-based microinstrumentation systems

    Get PDF
    A local smart bus is described which is designed for use in muti-chip-composed microinstrumentation system. The bus is able to transmit a digital code, bitstream, analog voltage, frquency, duty-cycle and also provides calibration facilities, service request and interrupt request modes.FC

    A low-power low-voltage digital bus interface for MCM-based microsystems

    Get PDF
    Comunicação apresentada na 23rd European Solid-State Circuits Conference (ESSCIRC '97), Southampton, UK, 16-18 September 1997.This paper describes a digital local bus interface, which is designed for use in a multi-chip-composed microsystem. The chip area using a CMOS 1.6mm n-well technology is 1mm2. Power consumption at 5V@100kHz is less than 500mW and for 5V@4MHz less than 2mW due to a smart power management of all functional blocks. The bus interface is able to transmit a digital code, bitstream, analog voltage, frequency, duty-cycle and also provides calibration facilities, service request and interrupt request for the smart sensors or microactuators.Junta Nacional de Investigação Científica e Tecnológica - Praxis XXI-BD/5181/95. STW - Project DEL 55.3733. TUDelft

    Quotient probabilistic normed spaces and completeness results

    Get PDF
    Quotient spaces of probabilistic normed spaces have never been considered. This note is a first attempt to fill this gap: the quotient space of a PN space with respect to one of its subspaces is introduced and its properties are studied. Finally, we investigate the completeness relationship among the PN spaces considered

    Adaptive Anomaly Detection via Self-Calibration and Dynamic Updating

    Get PDF
    The deployment and use of Anomaly Detection (AD) sensors often requires the intervention of a human expert to manually calibrate and optimize their performance. Depending on the site and the type of traffic it receives, the operators might have to provide recent and sanitized training data sets, the characteristics of expected traffic (i.e. outlier ratio), and exceptions or even expected future modifications of system's behavior. In this paper, we study the potential performance issues that stem from fully automating the AD sensors' day-to-day maintenance and calibration. Our goal is to remove the dependence on human operator using an unlabeled, and thus potentially dirty, sample of incoming traffic. To that end, we propose to enhance the training phase of AD sensors with a self-calibration phase, leading to the automatic determination of the optimal AD parameters. We show how this novel calibration phase can be employed in conjunction with previously proposed methods for training data sanitization resulting in a fully automated AD maintenance cycle. Our approach is completely agnostic to the underlying AD sensor algorithm. Furthermore, the self-calibration can be applied in an online fashion to ensure that the resulting AD models reflect changes in the system's behavior which would otherwise render the sensor's internal state inconsistent. We verify the validity of our approach through a series of experiments where we compare the manually obtained optimal parameters with the ones computed from the self-calibration phase. Modeling traffic from two different sources, the fully automated calibration shows a 7.08% reduction in detection rate and a 0.06% increase in false positives, in the worst case, when compared to the optimal selection of parameters. Finally, our adaptive models outperform the statically generated ones retaining the gains in performance from the sanitization process over time

    A microinstrumenation system for industrial applications

    Get PDF
    This paper describes the development of a microinstrumentation system in silicon containing all the components of the data acquisition system, such as sensors, signal-conditioning circuits, analog-digital converter, interface circuits, sensor bus interface, and an embedded microcontroller (MCU). The microinstrumentation system is to be fabricated using the Multi-Chip-Module (MCM) technology based on a chip-level infrastructure. A standard silicon platform is the floorplan for individual smart sensor die attachment and an on-chip local sensor bus interface, testing facilities, optional compatible sensors (such as thermal sensors). The microinstrumentation system is controlled by a MCU with several modes of low-power operation (inclusive stand-by mode). As the intended application requires a huge amount of data-processing, a RISC-type MCU architecture is to be used. The MCU communicates with the front-end sensors via a two-line (clock and data lines) intramodule sensor bus (Integrated Smart Sensor bus). The sensor scan rate is adaptive and can be event triggered. This upgraded version of the ISS bus allows: service and interrupt request from the sensors, test and calibration facilities. However, the additional functionality requires a third line. The MCU also controls the power consumption and the thermal budget of all system. This paper also presents three applications for the microinstrumentation system: condition monitoring of machines, an inertial navigation system and a miniature spectrometer.STW - Project DEL55.3733. TUDelft. Junta Nacional de Investigação Científica e Tecnológica - Praxis XXI-BD/5181/95
    corecore