Paul Farago

An OTA-C field programmable analog array for multi-mode filtering applications

This paper presents a reconfigurable analog array and its possible application in multi mode wireless communication equipments. The array is built around configurable analog blocks comprised of linearized, fully differential transconductance amplifiers. The circuit sacrifices a degree of generality in favor of specialized filtering operations at high frequencies, low consumption and good linearity, all required in modern communication devices. The programming of the filter frequency parameters is achieved through binary weighted transconductor arrays and a capacitance scaling circuit. The proposed analog array has been simulated at transistor level by using the Eldo simulation engine on a 90nm digital CMOS process.

An evolutionary approach to design and calibration of reconfigurable OTA-C filters

Latest trends in communication and consumer electronics target the development of fully adaptive systems on mixed signal systems-on-chip. This paper proposes an evolutionary approach to adaptive filter design. The hardware support of the evolutionary design algorithm is a field programmable analog array (FPAA). The FPAA has been implemented with OTA-C techniques. The synthesis algorithm has been developed considering the particularities of the proposed FPAA and of the supported filter structures. Topological reconfiguration is performed with a lookup table, parametric design is performed with evolutionary computation methods and wide-band self-calibration is achieved by means of a phase locked loop. The filter sizing algorithm is suitable for both intrinsic or extrinsic evolution and has the potential to be hard-wired in dedicated digital circuitry. Extensive transistor level simulations performed on the evolved adaptive filters prove the functionality of the proposed software and the underlying circuitry.

An Evolutionary Multi-objective Optimization Approach to Design the Sound Processor of a Hearing Aid

Hearing impairment is one of the most common problems nowadays which affects the quality of life in terms of speech understanding and communication abilities. Therefore, untreated hearing loss may negatively impact social life. Mild to moderate hearing loss may be compensated by employing a hearing aid. The hearing aid performs sub-band division of the auditory signal, and then amplifies each sub-band in order to correct the patient’s audiogram. Designing the hearing aid sound processor for optimal audiogram correction requires the determination of the number of sub-bands, filter order and sub-band gains respectively. Considering the conflicting nature between solution quality and hardware resources, designing the sound processor is a matter of compromise. This article proposes an evolutionary approach to designing the sound processor, which treats the design as a multi-objective optimization (MOO) problem. Thus, the sub-band number, the sub-band filter order and the audiogram correction function are simultaneously optimized. The determination of the subband gains, for a given configuration of sub-band number and filter order, is treated as a single-objective optimization (SOO) problem. Dedicated genetic algorithms (GA) are used to solve both MOO and SOO problems. The MOO was handled with the Pareto frontier method. The functionality of the proposed design algorithm is illustrated on two conclusive design examples for optimal audiogram correction.

A double-layer genetic algorithm for Gm-C filter design

Although analog circuits play an important role in Systemson-a-chip, their design is effort and time consuming. Automated design methodologies are elaborated to overcome drawbacks resulting from human design. This paper proposes a double-layer on-line genetic algorithm-based optimization method for use in the automated design of Gm-C filters. To accomplish on-line circuit evolution, a Matlab-Eldo interface is proposed for communication of the GA with the circuit simulation environment. After a presentation of the Gm-C filter with an analysis of filter tunability, the two layers of the evolution are presented: raw filter design and fine-tuning of the filter characteristic. Simulation of the evolutionary algorithm proves the efficiency of the double-layer approach in reducing design time for a GA-only optimization technique.

Neural networks and wavelet transform in waveform approximation

To fully analyze the time response of a complex system, in order to discover its critical operation points, the output waveform (under all conceivable conditions) needs to be generated. Using conventional methods as physical experiments or detailed simulations can be prohibitive from the resources point of view (time, equipment). The challenge is to generate the waveform by its numerous time samples as a function of different operating conditions described by a set of parameters. In this paper, we propose a fast to evaluate, but also accurate model that approximates the waveforms, as a reliable substitute for complex physical experiments or overwhelming system simulations. Our proposed model consists of two stages. In the first stage, a previously trained artificial neural network produces some coefficients standing for “primary” coefficients of a wavelet transform. In the second stage, an inverse wavelet transform generates all the time samples of the expected waveform, using a fusion between the “primary” coefficients and some “secondary” coefficients previously extracted from the nominal waveform in the family. The test results for a number of 100 different combinations of three waveform parameters show that our model is a reliable one, featuring high accuracy and generalization capabilities, as well as high computation speed.

Device mismatch analysis and effect compensation in fundamental analog cells

The operation of highly complex analog ICs is strongly affected by the non-idealities inherently induced in modern sub-micron production technologies. Extensive testing has proven that process mismatch of small geometry transistors has the strongest effect on production yield. The aim of this article is to propose a methodology to analyze and compensate the effects of mismatch on the functionality of basic analog building blocks, which will be reflected in the operation and performance of more complex analog ICs. The novelty of this paper is the bi-univocal treatment of mismatch cause and effect, along with the appropriate optimization strategy. The analysis methodology is developed around Monte Carlo simulation to estimate statistical data regarding post-production IC performance, and consequently production yield. Further on, means of compensation towards error enhancement are investigated and proven on basic analog building blocks, as well as on a fully differential folded-cascode operational transconductance amplifier.

An electronically programmable current balancing instrumentation amplifier for biomedical monitoring

Instrumentation amplifiers (IA) used in wearable biomedical monitoring systems have to satisfy several performance requirements, such as low-voltage supply and low-power consumption, enabling increased portability. In the same time, a very important feature is wide range parameter programmability. This paper proposes a solution to implement electronic gain programming into an IA. The proposed solution is developed around the current balancing concept. An electronically tunable transconductance amplifier is used for adjusting the IA voltage gain as a function of the transconductor bias currents. Additionally, the proposed IA outputs a differential signal, useful for latter differential analog signal processing. Simulation results validate the proposed IA.

Distributed fluorescent optical fiber proximity sensor: Towards a proof of concept

Fluorescent fibers are optical fibers which emit light as a response to an incident phenomenon, usually an incident light. Operation depends on the doping dyes, which determine specific fluorescence and optical characteristics useful in the development of optical sensors. In this work we propose a low-cost distributed proximity sensor implemented using a red fluorescent fiber, to provide a security option for a surface plasmon resonance system. Operation of the proposed sensor relies on having the incident illumination intensity varied by the presence or absence of an obstacle in the vicinity of the sensing element. This will influence the radiated fluorescence accordingly. The proposed setup for the implementation of the optical proximity sensor assumes having a high brightness LED deployed for axial fiber illumination and a blue LED for side illumination. Electronic processing then accounts for gain and digitization. Measurement results of the prototype validate the proposed concept.

Fluorescent fiber implementation of a high-resolution distributed position sensor

Fluorescent optical fibers employ the luminescence property of fluorescent dyes in order to radiate light as a response to incident illumination. When multiple dyes are used to dope the fiber, fluorescence results from the energy transfer between the donor and acceptor dyes and the reabsorption process. In this work we propose a high-resolution distributed optical sensor for position monitoring developed around a yellow fluorescent fiber. Immunity vs. ambient light variations is achieved by employing the spectral behavior of the donoracceptor energy transfer mechanism and the reabsorption process. This consists in a red shift of the fiber emission peaks vs. distance. Extensive experimentation with the laboratory proof of principle validates the proposed solution. Measurements carried out in laboratory environment under ambient illumination show that the wavelength of the emission peaks is insensitive to the intensity of the incident light, but is dependent on the variation of the ambient light color. Accordingly, rather than monitoring the wavelengths of the emission peaks, the proposed positions sensor evaluates the spectral spacing between the peaks. This provides an accurate estimate of the distance between the fiber end and the incident light application point. The proposed sensor exhibits a monotonous decrease of the spectral spacing vs. distance, which is indeed insensitive to limited variation of the ambient light.

Optical data transmission with plastic scintillating fibers

In data transmission systems there are applications where lateral coupling light is requested. Fluorescent optical fibers radiate light as a response to incident illumination along the side. Because of photosensitivity along the side, the plastic photo-luminescent fiber is considered a flexible coupling alternative of the light, instead of discrete position coupler or tap. Fluorescent optical fibers have been investigated for data transmission applications. With commercially available fluorescent fiber for the optical bus system and smartphone based data transmission (ASK modulation) the data rates up to 500Mbit/s are feasible, by selecting the right parameters such as short fluorescence lifetime, spectral region of the fibers correlated with light sources and photodetectors and in-fiber low spectral attenuation. The application is useful in automotive applications for data transmission and distributed sensing.