Simone Orcioni

Parametric yield formulation of MOS IC's affected by mismatch effect

A rigorous formulation of the parametric yield for very large scale integration (VLSI) designs including the mismatch effect is proposed. The theory has been carried out starting from a general statistical model relating random variations of device parameters to the stochastic behavior of process parameters. The model predicts a dependence of correlation, between devices fabricated in the same die, on their dimensions and mutual distances so that mismatch between equally designed devices can be considered as a particular case of such a model. As an application example, a new model for the autocorrelation function is proposed from which the covariance matrix of the parameters is derived. By assuming a linear approximation, a suitable formulation of the parametric yield for VLSI circuit design is obtained in terms of the covariance matrix of parameters.

On the approximation of stochastic processes by approximate identity neural networks

The ability of a neural network to learn from experience can be viewed as closely related to its approximating properties. By assuming that environment is essentially stochastic it follows that neural networks should be able to approximate stochastic processes. The aim of this paper is to show that some classes of artificial neural networks exist such that they are capable of providing the approximation, in the mean square sense, of prescribed stochastic processes with arbitrary accuracy. The networks so defined constitute a new model for neural processing and extend previous results concerning approximating capabilities of artificial neural networks.

Advances in Lee--Schetzen Method for Volterra Filter Identification

This paper concerns the identification of nonlinear discrete causal systems that can be approximated with the Wiener–Volterra series. Some advances in the efficient use of Lee–Schetzen (L–S) method are presented, which make practical the estimate of long memory and high order models. Major problems in L–S method occur in the identification of diagonal kernel elements. Two approaches have been considered: approximation of gridded data, with interpolation or smoothing, and improved techniques for diagonal elements estimation. A comparison of diagonal elements estimated, with different methods has been shown with extended tests on fifth order Volterra systems.

System-level power analysis methodology applied to the AMBA AHB bus [SoC applications]

The specification on power consumption of a digital system is extremely important due to the growing relevance of the market of portable devices and must be taken into account since the early phases of a complex system-on-chip design. In this paper, some guidelines are provided for the integration of the information on power consumption in the executable model of parameterized cores, with particular attention to the AMBA AHB bus. This gives important information for the analysis and choice between different design architectures driven by functional, timing and power constraints of the system-on-chip.

Instruction based power consumption estimation methodology

The paper presents a new model of the dynamic power dissipated by a circuit described at gate or behavioural level. A procedure is presented for an accurate estimate of the power dissipated during the execution of each instruction by using gate level or behavioural level digital simulations. The information on power consumption stored in a look-up table can be used in a system level simulation. The methodology has been applied to the design of an I/sup 2/C bus driver.

Analysis of the EMG Signal During Cyclic Movements Using Multicomponent AM–FM Decomposition

Sport, fitness, as well as rehabilitation activities, often require the accomplishment of repetitive movements. The correctness of the exercises is often related to the capability of maintaining the required cadence and muscular force. Failure to maintain the required force, also known as muscle fatigue, is accompanied by a shift in the spectral content of the surface electromyography (EMG) signal toward lower frequencies. This paper presents a novel approach for simultaneously obtaining exercise repetition frequency and evaluating muscular fatigue, as functions of time, by only using the EMG signal. The mean frequency of the amplitude spectrum (MFA) of the EMG signal, considered as a function of time, is directly related to the dynamics of the movement performed and to the fatigue of the involved muscles. If the movement is cyclic, MFA will display the same pattern and its average will tend to decrease. These two effects have been simultaneously modeled by a two-component AM-FM model based on the Hilbert transform. The method was tested on signals recorded using a wireless system applied to healthy subjects performing dumbbell biceps curls, dumbbell lateral rises, and bodyweight squats. Experimental results show the excellent performance of the proposed technique.

SystemC-WMS: Mixed-Signal Simulation Based on Wave Exchanges

This chapter proposes a methodology for extending SystemC to mixed-signal systems, aimed at allowing the reuse of analog models and to the simulation of heterogeneous systems. To this end, a general method for modeling analog modules using wave quantities is suggested, and a new kind of port and channel suitable to let modules communicate through waves have been defined. These entities are plugged directly on top of the standard SystemC kernel, so as to allow a seamless integration with the preexisting simulation environment, and are designed to permit total interconnection freedom to ease the development of reusable analog libraries.

A current mode multistable memory using asynchronous successive approximation A/D converters

In this work a multistable circuit for current memorization is presented. The technique used is based on a new type of asynchronous successive approximation A/D converter. The circuit has been implemented in a 0.8 /spl mu/m CMOS technology.

System-level energy estimation with Powersim

The present paper proposes a SystemC class library aimed to the calculation of energy consumption of hardware described at system level. To this end C++ operators are monitored and different energy models are used for each data type. This method does not require any change in the application source code. An application example with measures is proposed.

SiSMA-a tool for efficient analysis of analog CMOS integrated circuits affected by device mismatch

In this paper a simulator for the statistical analysis of analog CMOS integrated circuits affected by technological tolerance effects, including device mismatch, is presented. The tool, able to perform dc, ac, and transient analyses, is based on a rigorous formulation of circuit equations starting from the modified nodal analysis and including random current sources to take into account technological tolerances. Statistical simulation of specific circuits shows that the simulator requires a simulation time several orders of magnitude lower than that required by Monte Carlo analysis, while ensuring a good accuracy.