Redundant analog to digital conversion architectures in CMOS technology

The operation of modern electronic devices in different fields as communications, signal processing, and sensor interface is critically affected with robust, high performance and scalable Analog-to-Digital Converter (ADCs), that can be considered as one of the main blocks in many systems, since they are mandatory to make the link between the analog outside world and the evermore-ubiquitous digital computer world. The design of these ADCs come distinct tradeoffs between speed, power, resolution, and die area embodied within many data conversion architectural variations. The flash ADC structure are often the base structure for high-speed operation and simple architecture analog-to-digital converters (ADCs). As the input signal is applied to (

Redundant analog to digital conversion architectures in CMOS technology

The operation of modern electronic devices in different fields as communications, signal processing, and sensor interface is critically affected with robust, high performance and scalable Analog-to-Digital Converter (ADCs), that can be considered as one of the main blocks in many systems, since they are mandatory to make the link between the analog outside world and the evermore-ubiquitous digital computer world. The design of these ADCs come distinct tradeoffs between speed, power, resolution, and die area embodied within many data conversion architectural variations. The flash ADC structure are often the base structure for high-speed operation and simple architecture analog-to-digital converters (ADCs). As the input signal is applied to (

A built-in self-test technique for high speed analog-to-digital converters

Fundação para a Ciência e a Tecnologia (FCT) - PhD grant (SFRH/BD/62568/2009

A high-speed, folding, analog-to-digital converter

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (leaves 99-100).by Paul Louis.M.S

Development of a 6-bit 15.625 MHz CMOS two-step flash analog-to-digital converter for a low dead time sub-nanosecond time measurement system

The development of a 6-bit 15.625 MHz CMOS two-step analog-to-digital converter (ADC) is presented. The ADC was developed for use in a low dead time, high-performance, sub-nanosecond time-to-digital converter (TDC). The TDC is part of a new custom CMOS application specific integrated circuit (ASIC) that will be incorporated in the next generation of front-end electronics for high-performance positron emission tomography imaging. The ADC is based upon a two-step flash architecture that reduces the comparator count by a factor-of-two when compared to a traditional flash ADC architecture and thus a significant reduction in area, power dissipation, and input capacitance of the converter is achieved. The converter contains time-interleaved auto-zeroed CMOS comparators. These comparators utilize offset correction in both the preamplifier and the subsequent regenerative latch stage to guarantee good integral and differential non-linearity performance of the converter over extreme process conditions. Also, digital error correction was employed to overcome most of the major metastability problems inherent in flash converters and to guarantee a completely monotonic transfer function. Corrected comparator offset measurements reveal that the CMOS comparator design maintains a worse case input-referred offset of less than 1 mV at conversion rates up to 8 MHz and less than a 2 mV offset at conversion rates as high as 16 MHz while dissipating less than 2.6 mW. Extensive laboratory measurements indicate that the ADC achieves differential and integral non-linearity performance of less than ±1/2 LSB with a 20 mV/LSB resolution. The ADC dissipates 90 mW from a single 5 V supply and occupies a die area of 1.97 mm x 1.13 mm in 0.8 μm CMOS technology

The CERES/NA45 Radial Drift Time Projection Chamber

The design, calibration, and performance of the first radial drift Time Projection Chamber (TPC) are presented. The TPC was built and installed at the CERES/NA45 experiment at the CERN SPS in the late nineties, with the objective to improve the momentum resolution of the spectrometer. The upgraded experiment took data twice, in 1999 and in 2000. After a detailed study of residual distortions a spatial resolution of 340 um in the azimuthal and 640 um in the radial direction was achieved, corresponding to a momentum resolution of Dp/p = sqrt{(1% * p/GeV)^2 + (2%)^2}.Comment: 57 pages, 59 figure

Electronics for Sensors

The aim of this Special Issue is to explore new advanced solutions in electronic systems and interfaces to be employed in sensors, describing best practices, implementations, and applications. The selected papers in particular concern photomultiplier tubes (PMTs) and silicon photomultipliers (SiPMs) interfaces and applications, techniques for monitoring radiation levels, electronics for biomedical applications, design and applications of time-to-digital converters, interfaces for image sensors, and general-purpose theory and topologies for electronic interfaces

A Low-Power, Reconfigurable, Pipelined ADC with Automatic Adaptation for Implantable Bioimpedance Applications

Biomedical monitoring systems that observe various physiological parameters or electrochemical reactions typically cannot expect signals with fixed amplitude or frequency as signal properties can vary greatly even among similar biosignals. Furthermore, advancements in biomedical research have resulted in more elaborate biosignal monitoring schemes which allow the continuous acquisition of important patient information. Conventional ADCs with a fixed resolution and sampling rate are not able to adapt to signals with a wide range of variation. As a result, reconfigurable analog-to-digital converters (ADC) have become increasingly more attractive for implantable biosensor systems. These converters are able to change their operable resolution, sampling rate, or both in order convert changing signals with increased power efficiency. Traditionally, biomedical sensing applications were limited to low frequencies. Therefore, much of the research on ADCs for biomedical applications focused on minimizing power consumption with smaller bias currents resulting in low sampling rates. However, recently bioimpedance monitoring has become more popular because of its healthcare possibilities. Bioimpedance monitoring involves injecting an AC current into a biosample and measuring the corresponding voltage drop. The frequency of the injected current greatly affects the amplitude and phase of the voltage drop as biological tissue is comprised of resistive and capacitive elements. For this reason, a full spectrum of measurements from 100 Hz to 10-100 MHz is required to gain a full understanding of the impedance. For this type of implantable biomedical application, the typical low power, low sampling rate analog-to-digital converter is insufficient. A different optimization of power and performance must be achieved. Since SAR ADC power consumption scales heavily with sampling rate, the converters that sample fast enough to be attractive for bioimpedance monitoring do not have a figure-of-merit that is comparable to the slower converters. Therefore, an auto-adapting, reconfigurable pipelined analog-to-digital converter is proposed. The converter can operate with either 8 or 10 bits of resolution and with a sampling rate of 0.1 or 20 MS/s. Additionally, the resolution and sampling rate are automatically determined by the converter itself based on the input signal. This way, power efficiency is increased for input signals of varying frequency and amplitude

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Department of Electrical EngineeringA Sensor system is advanced along sensor technologies are developed. The performance improvement of sensor system can be expected by using the internet of things (IoT) communication technology and artificial neural network (ANN) for data processing and computation. Sensors or systems exchanged the data through this wireless connectivity, and various systems and applications are possible to implement by utilizing the advanced technologies. And the collected data is computed using by the ANN and the efficiency of system can be also improved. Gas monitoring system is widely need from the daily life to hazardous workplace. Harmful gas can cause a respiratory disease and some gas include cancer-causing component. Even though it may cause dangerous situation due to explosion. There are various kinds of hazardous gas and its characteristics that effect on human body are different each gas. The optimal design of gas monitoring system is necessary due to each gas has different criteria such as the permissible concentration and exposure time. Therefore, in this thesis, conventional sensor system configuration, operation, and limitation are described and gas monitoring system with wireless connectivity and neural network is proposed to improve the overall efficiency. As I already mentioned above, dangerous concentration and permissible exposure time are different depending on gas types. During the gas monitoring, gas concentration is lower than a permissible level in most of case. Thus, the gas monitoring is enough with low resolution for saving the power consumption in this situation. When detecting the gas, the high-resolution is required for the accurate concentration detecting. If the gas type is varied in the above situation, the amount of calculation increases exponentially. Therefore, in the conventional systems, target specifications are decided by the highest requirement in the whole situation, and it occurs increasing the cost and complexity of readout integrated circuit (ROIC) and system. In order to optimize the specification, the ANN and adaptive ROIC are utilized to compute the complex situation and huge data processing. Thus, gas monitoring system with learning-based algorithm is proposed to improve its efficiency. In order to optimize the operation depending on situation, dual-mode ROIC that monitoring mode and precision mode is implemented. If the present gas concentration is decided to safe, monitoring mode is operated with minimal detecting accuracy for saving the power consumption. The precision mode is switched when the high-resolution or hazardous situation are detected. The additional calibration circuits are necessary for the high-resolution implementation, and it has more power consumption and design complexity. A high-resolution Analog-to-digital converter (ADC) is kind of challenges to design with efficiency way. Therefore, in order to reduce the effective resolution of ADC and power consumption, zooming correlated double sampling (CDS) circuit and prediction successive approximation register (SAR) ADC are proposed for performance optimization into precision mode. A Microelectromechanical systems (MEMS) based gas sensor has high-integration and high sensitivity, but the calibration is needed to improve its low selectivity. Conventionally, principle component analysis (PCA) is used to classify the gas types, but this method has lower accuracy in some case and hard to verify in real-time. Alternatively, ANN is powerful algorithm to accurate sensing through collecting the data and training procedure and it can be verified the gas type and concentration in real-time. ROIC was fabricated in complementary metal-oxide-semiconductor (CMOS) 180-nm process and then the efficiency of the system with adaptive ROIC and ANN algorithm was experimentally verified into gas monitoring system prototype. Also, Bluetooth supports wireless connectivity to PC and mobile and pattern recognition and prediction code for SAR ADC is performed in MATLAB. Real-time gas information is monitored by Android-based application in smartphone. The dual-mode operation, optimization of performance and prediction code are adjusted with microcontroller unit (MCU). Monitoring mode is improved by x2.6 of figure-of-merits (FoM) that compared with previous resistive interface.clos