15 research outputs found

    Novel CCII-based Field Programmable Analog Array and its Application to a Sixth-Order Butterworth LPF

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    In this paper, a field programmable analog array (FPAA) is proposed. The proposed FPAA consists of seven configurable analog blocks (CABs) arranged in a hexagonal lattice such that the CABs are directly connected to each other. This structure improves the overall frequency response of the chip by decreasing the parasitic capacitances in the signal path. The CABS of the FPAA is based on a novel fully differential digitally programmable current conveyor (DPCCII). The programmability of the DPCCII is achieved using digitally controlled three-bit MOS ladder current division network. No extra biasing circuit is required to generate specific analog control voltage signals. The DPCCII has constant standby power consumption, offset voltage, bandwidth and harmonic distortions over all its programming range. A sixth-order Butterworth tunable LPF suitable for WLAN/WiMAX receivers is realized on the proposed FPAA. The filter power consumption is 5.4mW from 1V supply; it’s cutoff frequency is tuned from 5.2 MHz to 16.9 MHz. All the circuits are realized using 90nm CMOS technology from TSMC. All simulations are carried out using Cadence

    A wideband linear tunable CDTA and its application in field programmable analogue array

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    This document is the Accepted Manuscript version of the following article: Hu, Z., Wang, C., Sun, J. et al. ‘A wideband linear tunable CDTA and its application in field programmable analogue array’, Analog Integrated Circuits and Signal Processing, Vol. 88 (3): 465-483, September 2016. Under embargo. Embargo end date: 6 June 2017. The final publication is available at Springer via https://link.springer.com/article/10.1007%2Fs10470-016-0772-7 © Springer Science+Business Media New York 2016In this paper, a NMOS-based wideband low power and linear tunable transconductance current differencing transconductance amplifier (CDTA) is presented. Based on the NMOS CDTA, a novel simple and easily reconfigurable configurable analogue block (CAB) is designed. Moreover, using the novel CAB, a simple and versatile butterfly-shaped FPAA structure is introduced. The FPAA consists of six identical CABs, and it could realize six order current-mode low pass filter, second order current-mode universal filter, current-mode quadrature oscillator, current-mode multi-phase oscillator and current-mode multiplier for analog signal processing. The Cadence IC Design Tools 5.1.41 post-layout simulation and measurement results are included to confirm the theory.Peer reviewedFinal Accepted Versio

    Analog Reconfigurable Circuits

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    The aim of this paper is to present an overview of a new branch of analog electronics represented by analog reconfigurable circuits. The reconfiguration of analog circuits has been known and used since the beginnings of electronics, but the universal reconfigurable circuits called Field Programmable Analog Arrays (FPAA) have been developed over the last two decades. This paper presents the classification of analog circuit reconfiguration, examples of FPAA solutions obtained as academic projects and commercially available ones, as well as some application examples of the dynamic reconfiguration of FPAA.

    Analog signal processing on a reconfigurable platform

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    The Cooperative Analog/Digital Signal Processing (CADSP) research group's approach to signal processing is to see what opportunities lie in adjusting the line between what is traditionally computed in digital and what can be done in analog. By allowing more computation to be done in analog, we can take advantage of its low power, continuous domain operation, and parallel capabilities. One setback keeping Analog Signal Processing (ASP) from achieving more wide-spread use, however, is its lack of programmability. The design cycle for a typical analog system often involves several iterations of the fabrication step, which is labor intensive, time consuming, and expensive. These costs in both time and money reduce the likelihood that engineers will consider an analog solution. With CADSP's development of a reconfigurable analog platform, a Field-Programmable Analog Array (FPAA), it has become much more practical for systems to incorporate processing in the analog domain. In this Thesis, I present an entire chain of tools that allow one to design simply at the system block level and then compile that design onto analog hardware. This tool chain uses the Simulink design environment and a custom library of blocks to create analog systems. I also present several of these ASP blocks, covering a broad range of functions from matrix computation to interfacing. In addition to these tools and blocks, the most recent FPAA architectures are discussed. These include the latest RASP general-purpose FPAAs as well as an adapted version geared toward high-speed applications.M.S.Committee Chair: Hasler, Paul; Committee Member: Anderson, David; Committee Member: Ghovanloo, Maysa

    Controller implementation using analog reconfigurable hardware (FPAA)

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    This Thesis has the main target to make a research about FPAA/dpASPs devices and technologies applied to control systems. These devices provide easy way to emulate analog circuits that can be reconfigurable by programming tools from manufactures and in case of dpASPs are able to be dynamically reconfigurable on the fly. It is described different kinds of technologies commercially available and also academic projects from researcher groups. These technologies are very recent and are in ramp up development to achieve a level of flexibility and integration to penetrate more easily the market. As occurs with CPLD/FPGAs, the FPAA/dpASPs technologies have the target to increase the productivity, reducing the development time and make easier future hardware reconfigurations reducing the costs. FPAA/dpAsps still have some limitations comparing with the classic analog circuits due to lower working frequencies and emulation of complex circuits that require more components inside the integrated circuit. However, they have great advantages in sensor signal condition, filter circuits and control systems. This thesis focuses practical implementations of these technologies to control system PID controllers. The result of the experiments confirms the efficacy of FPAA/dpASPs on signal condition and control systems.Esta tese tem como principal objectivo fazer uma pesquisa sobre circuitos integrados e tecnologias das FPAA/dpASPs aplicadas a sistemas de controlo. Estes dispositivos possibilitam a emulação de circuitos analógicos que podem ser reconfiguráveis por ferramentas de programação dos próprios fabricantes e no caso dos dpASPs são capazes de ser dinamicamente reconfiguráveis em tempo real. São descritas diferentes tecnologias disponíveis no mercado e também projectos académicos de grupos de investigação. Estas tecnologias são muito recentes e estão em pleno desenvolvimento para alcançar um nível de flexibilidade e integração para penetrar mais facilmente no mercado. Como já ocorre com as CPLD/FPGAs, os FPAA/dpASPs tem o objectivo de aumentar a produtividade, reduzindo o tempo de desenvolvimento e facilitar reconfigurações futuras de hardware, reduzindo os custos. As FPAA/dpASPs ainda tem algumas limitações comparando com os circuitos analógicos clássicos devido a uma menor largura de banda de frequências de trabalho e à dificuldade de emulação de circuitos complexos que requerem mais componentes dentro do circuito integrado e portanto uma maior escala de integração. No entanto, estes circuitos integrados têm grandes vantagens e podem ser utilizados para aplicações de condicionamento do sinal de sensores, circuitos de filtros e sistemas de controlo. Esta tese concentra-se nas implementações práticas destas tecnologias aos sistemas de controlo usando controladores PID. Os resultados das experiências confirmam a eficácia das FPAA/dpASPs no condicionamento de sinal e sistemas de controlo

    Configurable analog hardware for neuromorphic Bayesian inference and least-squares solutions

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    Sparse approximation is a Bayesian inference program with a wide number of signal processing applications, such as Compressed Sensing recovery used in medical imaging. Previous sparse coding implementations relied on digital algorithms whose power consumption and performance scale poorly with problem size, rendering them unsuitable for portable applications, and a bottleneck in high speed applications. A novel analog architecture, implementing the Locally Competitive Algorithm (LCA), was designed and programmed onto a Field Programmable Analog Arrays (FPAAs), using floating gate transistors to set the analog parameters. A network of 6 coefficients was demonstrated to converge to similar values as a digital sparse approximation algorithm, but with better power and performance scaling. A rate encoded spiking algorithm was then developed, which was shown to converge to similar values as the LCA. A second novel architecture was designed and programmed on an FPAA implementing the spiking version of the LCA with integrate and fire neurons. A network of 18 neurons converged on similar values as a digital sparse approximation algorithm, with even better performance and power efficiency than the non-spiking network. Novel algorithms were created to increase floating gate programming speed by more than two orders of magnitude, and reduce programming error from device mismatch. A new FPAA chip was designed and tested which allowed for rapid interfacing and additional improvements in accuracy. Finally, a neuromorphic chip was designed, containing 400 integrate and fire neurons, and capable of converging on a sparse approximation solution in 10 microseconds, over 1000 times faster than the best digital solution.Ph.D

    Low-Power and Programmable Analog Circuitry for Wireless Sensors

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    Embedding networks of secure, wirelessly-connected sensors and actuators will help us to conscientiously manage our local and extended environments. One major challenge for this vision is to create networks of wireless sensor devices that provide maximal knowledge of their environment while using only the energy that is available within that environment. In this work, it is argued that the energy constraints in wireless sensor design are best addressed by incorporating analog signal processors. The low power-consumption of an analog signal processor allows persistent monitoring of multiple sensors while the device\u27s analog-to-digital converter, microcontroller, and transceiver are all in sleep mode. This dissertation describes the development of analog signal processing integrated circuits for wireless sensor networks. Specific technology problems that are addressed include reconfigurable processing architectures for low-power sensing applications, as well as the development of reprogrammable biasing for analog circuits
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