Current-Mode Techniques for the Implementation of Continuous- and Discrete-Time Cellular Neural Networks

This paper presents a unified, comprehensive approach to the design of continuous-time (CT) and discrete-time (DT) cellular neural networks (CNN) using CMOS current-mode analog techniques. The net input signals are currents instead of voltages as presented in previous approaches, thus avoiding the need for current-to-voltage dedicated interfaces in image processing tasks with photosensor devices. Outputs may be either currents or voltages. Cell design relies on exploitation of current mirror properties for the efficient implementation of both linear and nonlinear analog operators. These cells are simpler and easier to design than those found in previously reported CT and DT-CNN devices. Basic design issues are covered, together with discussions on the influence of nonidealities and advanced circuit design issues as well as design for manufacturability considerations associated with statistical analysis. Three prototypes have been designed for l.6-pm n-well CMOS technologies. One is discrete-time and can be reconfigured via local logic for noise removal, feature extraction (borders and edges), shadow detection, hole filling, and connected component detection (CCD) on a rectangular grid with unity neighborhood radius. The other two prototypes are continuous-time and fixed template: one for CCD and other for noise removal. Experimental results are given illustrating performance of these prototypes

Systematic Comparison of HF CMOS Transconductors

Transconductors are commonly used as active elements in high-frequency (HF) filters, amplifiers, mixers, and oscillators. This paper reviews transconductor design by focusing on the V-I kernel that determines the key transconductor properties. Based on bandwidth considerations, simple V-I kernels with few or no internal nodes are preferred. In a systematic way, virtually all simple kernels published in literature are generated. This is done in two steps: 1) basic 3-terminal transconductors are covered and 2) then five different techniques to combine two of them in a composite V-I kernel. In order to compare transconductors in a fair way, a normalized signal-to-noise ratio (NSNR) is defined. The basic V-I kernels and the five classes of composite V-I kernels are then compared, leading to insight in the key mechanisms that affect NSNR. Symbolic equations are derived to estimate NSNR, while simulations with more advanced MOSFET models verify the results. The results show a strong tradeoff between NSNR and transconductance tuning range. Resistively generated MOSFETs render the best NSNR results and are robust for future technology developments

Smart-Pixel Cellular Neural Networks in Analog Current-Mode CMOS Technology

This paper presents a systematic approach to design CMOS chips with concurrent picture acquisition and processing capabilities. These chips consist of regular arrangements of elementary units, called smart pixels. Light detection is made with vertical CMOS-BJT’s connected in a Darlington structure. Pixel smartness is achieved by exploiting the Cellular Neural Network paradigm [1], [2], incorporating at each pixel location an analog computing cell which interacts with those of nearby pixels. We propose a current-mode implementation technique and give measurements from two 16 x 16 prototypes in a single-poly double-metal CMOS n-well 1.6-µm technology. In addition to the sensory and processing circuitry, both chips incorporate light-adaptation circuitry for automatic contrast adjustment. They obtain smart-pixel densities up to 89 units/mm2, with a power consumption down to 105 µW/unit and image processing times below 2 µs

CMOS design of chaotic oscillators using state variables: a monolithic Chua's circuit

This paper presents design considerations for monolithic implementation of piecewise-linear (PWL) dynamic systems in CMOS technology. Starting from a review of available CMOS circuit primitives and their respective merits and drawbacks, the paper proposes a synthesis approach for PWL dynamic systems, based on state-variable methods, and identifies the associated analog operators. The GmC approach, combining quasi-linear VCCS's, PWL VCCS's, and capacitors is then explored regarding the implementation of these operators. CMOS basic building blocks for the realization of the quasi-linear VCCS's and PWL VCCS's are presented and applied to design a Chua's circuit IC. The influence of GmC parasitics on the performance of dynamic PWL systems is illustrated through this example. Measured chaotic attractors from a Chua's circuit prototype are given. The prototype has been fabricated in a 2.4- mu m double-poly n-well CMOS technology, and occupies 0.35 mm/sup 2/, with a power consumption of 1.6 mW for a +or-2.5-V symmetric supply. Measurements show bifurcation toward a double-scroll Chua's attractor by changing a bias current

Metodologia Per la Caratterizzazione di amplificatori a basso rumore per UMTS

In questo lavoro si presenta una metodologia di progettazione elettronica a livello di sistema, affrontando il problema della caratterizzazione dello spazio di progetto dell' amplificatore a basso rumore costituente il primo stadio di un front end a conversione diretta per UMTS realizzato in tecnologia CMOS con lunghezza di canale .18u. La metodologia è sviluppata al fine di valutare in modo quantititativo le specifiche ottime di sistema per il front-end stesso e si basa sul concetto di Piattaforma Analogica, che prevede la costruzione di un modello di prestazioni per il blocco analogico basato su campionamento statistico di indici di prestazioni del blocco stesso, misurati tramite simulazione di dimensionamenti dei componenti attivi e passivi soddisfacenti un set di equazioni specifico della topologia circuitale. Gli indici di prestazioni vengono successivamente ulizzati per parametrizzare modelli comportamentali utilizzati nelle fasi di ottimizzazione a livello di sistema. Modelli comportamentali atti a rappresentare i sistemi RF sono stati pertanto studiati per ottimizzare la scelta delle metriche di prestazioni. L'ottimizzazione dei set di equazioni atti a selezionare le configurazione di interesse per il campionamento ha al tempo stesso richiesto l'approfondimento dei modelli di dispositivi attivi validi in tutte le regioni di funzionamento, e lo studio dettagliato della progettazione degli amplificatori a basso rumore basati su degenerazione induttiva. Inoltre, il problema della modellizzazione a livello di sistema degli effetti della comunicazione tra LNA e Mixer è stato affrontato proponendo e analizzando diverse soluzioni. Il lavoro ha permesso di condurre un'ottimizzazione del front-end UMTS, giungendo a specifiche ottime a livello di sistema per l'amplificatore stesso

Simulation of intrinsic parameter fluctuations in decananometer and nanometer-scale MOSFETs

Intrinsic parameter fluctuations introduced by discreteness of charge and matter will play an increasingly important role when semiconductor devices are scaled to decananometer and nanometer dimensions in next-generation integrated circuits and systems. In this paper, we review the analytical and the numerical simulation techniques used to study and predict such intrinsic parameters fluctuations. We consider random discrete dopants, trapped charges, atomic-scale interface roughness, and line edge roughness as sources of intrinsic parameter fluctuations. The presented theoretical approach based on Green's functions is restricted to the case of random discrete charges. The numerical simulation approaches based on the drift diffusion approximation with density gradient quantum corrections covers all of the listed sources of fluctuations. The results show that the intrinsic fluctuations in conventional MOSFETs, and later in double gate architectures, will reach levels that will affect the yield and the functionality of the next generation analog and digital circuits unless appropriate changes to the design are made. The future challenges that have to be addressed in order to improve the accuracy and the predictive power of the intrinsic fluctuation simulations are also discussed

MOSFET ZTC condition analysis for a self-biased current reference design

In this paper a self-biased current reference based on Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) Zero Temperature Coefficient (ZTC) condition is proposed. It can be imple mented in any Complementary Metal-Oxide-Semiconductor (CMOS) fabrication process and pro vides another alternative to design current references. In order to support the circuit design, ZTC condition is analyzed using a MOSFET model that is continuous from weak to strong inversion, show ing that this condition always occurs from moderate to strong inversion in any CMOS process. The proposed topology was designed in a 180 nm process, operates with a supply voltage from 1.4V to 1.8 V and occupies around 0.010mm2 of silicon area. From circuit simulations our reference showed a temperature coefficient (TC) of 15 ppm/o C from -40 to +85o C, and a fabrication process sensitivity of σ/μ = 4.5% for the current reference, including average process and local mismatch variability analysis. The simulated power supply sensitivity is estimated around 1%/V

CMOS current-mode chaotic neurons

This paper presents two nonlinear CMOS current-mode circuits that implement neuron soma equations for chaotic neural networks, and another circuit to realize programmable current-mode synapse using CMOS-compatible BJT's. They have been fabricated in a double-metal, single-poly 1.6 /spl mu/m CMOS technology and their measured performance reached the expected function and specifications. The neuron soma circuits use a novel, highly accurate CMOS circuit strategy to realize piecewise-linear characteristics in the current-mode domain. Their prototypes obtain reduced area and low voltage power supply (down to 3 V) with clock frequency of 500 kHz. As regard to the synapse circuit, it obtains large linearity and continuous, linear, weight adjustment by exploration of the exponential-law operation of CMOS-BJT's. The full accordance observed between theory and measurements supports the development of future analog VLSI chaotic neural networks to emulate biological systems and advanced computation