A comprehensive high-level model for CMOS-MEMS resonators

2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a behavioral modeling technique for CMOS microelectromechanical systems (MEMS) microresonators that enables simulation of an MEMS resonator model in Analog Hardware Description Language format within a system-level circuit simulation. A 100-kHz CMOS-MEMS resonant pressure sensor has been modeled into Verilog-A code and successfully simulated within Cadence framework. Analysis has shown that simulation results of the reported model are in agreement with the device characterization results. As an application of the proposed methodology, simulation and results of the model together with an integrated monolithic low-noise amplifier is exemplified for detecting the position change of the resonator.Peer ReviewedPostprint (author's final draft

Analog VLSI implementation of kernel-based classifiers

Kernel-based classifiers are neural networks (radial basis functions) where the probability densities of each class of data are first estimated, to be used thereafter to approximate Bayes boundaries between classes. Such an algorithm however involves a large number of operations, and its parallelism makes it an ideal candidate for a dedicated VLSI implementation. The authors present in this paper the architecture for a dedicated processor for kernel-based classifiers, and the implementation of the original cells.Peer ReviewedPostprint (published version

Closed-form equation for natural frequencies of beams under full range of axial loads modeled with a spring-mass system

A new simple closed-form equation that accurately predicts the effect of an arbitrarily large constant axial load, residual stress or temperature shift on the natural frequencies of an uniform single-span beam, with various end conditions, is presented. Its accuracy and applicability range are studied by comparing its predictions with numerical simulations and with the approximate Galef’s and Bokaian’s formulas. The new equation may be understood as a refinement or extension of these two approximate formulas. Significant accuracy and applicability range improvements are achieved, especially near the buckling point and for large and moderate axial load. The new closed-form equation is applicable in the full range of axial load, i.e., from the buckling load to the tensioned-string limit. It also models well the beam-to-string transition region for the eight boundary conditions studied. It works remarkably well in the free-free and sliding-free cases, where it is a near-exact solution. In addition, it yields the natural frequencies of a 1-D spring-mass system that may be used to model tensioned beams, and potentially, more complex systems.Peer ReviewedPostprint (published version

LEGION-based image segmentation by means of spiking neural networks using normalized synaptic weights implemented on a compact scalable neuromorphic architecture

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/LEGION (Locally Excitatory, Globally Inhibitory Oscillator Network) topology has demonstrated good capabilities in scene segmentation applications. However, the implementation of LEGION algorithm requires machines with high performance to process a set of complex differential equations limiting its use in practical real-time applications. Recently, several authors have proposed alternative methods based on spiking neural networks (SNN) to create oscillatory neural networks with low computational complexity and highly feasible to be implemented on digital hardware to perform adaptive segmentation of images. Nevertheless, existing SNN with LEGION configuration focus on the membrane model leaving aside the behavior of the synapses although they play an important role in the synchronization of several segments by self-adapting their weights. In this work, we propose a SNN-LEGION configuration along with normalized weight of the synapses to self-adapt the SNN network to synchronize several segments of any size and shape at the same time. The proposed SNN-LEGION method involves a global inhibitor, which is in charge of performing the segmentation process between different objects with different sizes and shapes on time. To validate the proposal, the SNN-LEGION method is implemented on an optimized scalable neuromorphic architecture. Our preliminary results demonstrate that the proposed normalization process of the synaptic weights along with the SNN-LEGION configuration keep the capacity of the LEGION network to separate the segments on time, which can be useful in video processing applications such as vision processing systems for mobile robots, offering lower computational complexity and area consumption compared with previously reported solutions.The authors would like to thank the Consejo Nacional de Ciencia y Tecnologia (CONACyT) and the IPN for the financial support to realize this work under project SIP-20180251. This work was also supported in part by the Spanish Ministry of Science and Innovation and the European Social Fund (ESF) under Projects TEC2011-27047 and TEC2015-67278-R.Peer ReviewedPostprint (author's final draft

Curvature of BEOL cantilevers in CMOS-MEMS processes

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents the curvature characterization results of released back-end-of-line 5 µm-wide cantilevers for two different 0.18-µm 1P6M complementary metal-oxide semiconductor microelectromechanical systems processes. Results from different runs and lots from each foundry are presented. The methodology and accuracy of the characterization approach, based on optical measurements of test cantilever curvature, are also discussed. Special emphasis is given to the curvature average and variability as a function of the number of stacked layers. Analythical equations for modeling the bending behavior of stacked cantilevers as a function of the tungsten (W) vias that join the metal layers are presented. In addition, the effect of various post-processing conditions and design techniques on the curvature of both single and stacked cantilevers is analyzed. In particular, surpassing certain time-dependent temperature stress conditions after release lead to curvature shifts larger than one order of magnitude. Also, the W via design was found to strongly affect the curvature of the test cantilevers.Peer ReviewedPostprint (author's final draft

Sense/Drive Architecture for CMOS-MEMS Accelerometers with Relaxation Oscillator and TDC

Postprint (published version

Action potential propagation: ion current or intramembrane electric field?

The established action potential propagation mechanisms do not satisfactorily explain propagation on myelinated axons given the current knowledge of biological channels and membranes. The flow across ion channels presents two possible effects: the electric potential variations across the lipid bilayers (action potential) and the propagation of an electric field through the membrane inner part. The proposed mechanism is based on intra-membrane electric field propagation, this propagation can explain the action potential saltatory propagation and its constant delay independent of distance between Ranvier nodes in myelinated axons.Peer ReviewedPostprint (author's final draft

Translinear signal processing circuits in standard CMOS FPAA

In this paper, the implementation of signal processing circuits on a novel translinear Field-Programmable Analog Array (FPAA) testchip is reported. The FPAA testchip is based on a 0.35-micron, fully CMOS translinear element, which is the core block of a reconfigurable analog cell. The FPAA embeds a 5 5 cell array. As implementation examples, a four-quadrant multiplier with five decade dynamic range and a programmable fourth-order low-pass filter with up to 7 MHz bandwidth have been mapped on the translinear FPAA. 14 cells have been used for the four-quadrant multiplier while 18 cells were needed for the fourth-order low-pass filter.Postprint (published version

A mixed-signal control system for Lorentz-force resonant MEMS magnetometers

This paper presents a mixed-signal closed-loop control system for Lorentz force resonant MEMS magnetometers. The control system contributes to 1) the automatic phase control of the loop, that allows start-up and keeps self-sustained oscillation at the MEMS resonance frequency, and 2) output offset reduction due to electrostatic driving by selectively disabling it. The proposed solution proof-of-concept has been tested with a Lorentz force-based MEMS magnetometer. The readout electronic circuitry has been implemented on a printed circuit board with off-the-shelf components. Digital control has been implemented in an FPGA coded with VHDL. When biased with 1 V and a driving current of 300 µArms, the device shows 9.75 pA/µT sensitivity and total sensor white noise of 550 nT/vHz. Offset when electrostatic driving is disabled is 793 µT, which means a 40.1% reduction compared when electrostatic driving is enabled. Moreover, removing electrostatic driving does not worsen bias instability, which is lower than 125 nT in both driving cases.Peer ReviewedPostprint (published version

A test setup for the characterization of Lorentz-force MEMS magnetometers

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Lorentz-force MEMS magnetometers are interesting candidates for the replacement of magnetometers in consumer electronics products. Plenty of works in the literature propose MEMS magnetometers, their readout circuits and modulations. However, during the standalone characterization of such MEMS devices, a great variety of instruments and strategies are used, making it very complex to compare results from different works in the literature. For this reason, this article proposes a test setup to characterize Lorentz-force MEMS magnetometers. The proposed setup is based around the use of an impedance analyzer for the driving of voltage and Lorentz-current of the MEMS in-phase and in quadrature, which allows the device Amplitude Modulation and Frequency Modulation characterization. The proposed solution is validated by using the designed circuit to characterize two CMOS-MEMS magnetometers with very different characteristics.This work was supported in part by the Spanish Ministry of Science, Innovation and Universities, the State Research Agency (AEI) under Project RTI2018-099766-B-I00, and in part by the European Social Fund (ESF).Peer ReviewedPostprint (published version