Impact of mode localization on the motional resistance of coupled MEMS resonators

This paper investigates the effect of mode-localization that arises from structural asymmetry induced by manufacturing tolerances in mechanically coupled, electrically transduced Si MEMS resonators. We demonstrate that in the case of such mechanically coupled resonators, the achievable series motional resistance (R x) is dependent not only on the quality factor (Q) but also on the variations in the eigenvector of the chosen mode of vibration induced by mode localization due to manufacturing tolerances during the fabrication process. We study this effect of mode-localization both theoretically and experimentally in two pairs of coupled double-ended tuning fork resonators with different levels of initial structural asymmetry. The measured series R x is minimal when the system is close to perfect symmetry and any deviation from structural symmetry induced by fabrication tolerances leads to a degradation in the effective R x. Mechanical tuning experiments of the stiffness of one of the coupled resonators was also conducted to study variations in R x as a function of structural asymmetry within the system, the results of which demonstrated consistent variations in motional resistance with predictions. © 2012 IEEE.

Templates and anchors for antenna-based wall following in cockroaches and robots

The interplay between robotics and neuromechanics facilitates discoveries in both fields: nature provides roboticists with design ideas, while robotics research elucidates critical features that confer performance advantages to biological systems. Here, we explore a system particularly well suited to exploit the synergies between biology and robotics: high-speed antenna-based wall following of the American cockroach (Periplaneta americana). Our approach integrates mathematical and hardware modeling with behavioral and neurophysiological experiments. Specifically, we corroborate a prediction from a previously reported wall-following template - the simplest model that captures a behavior - that a cockroach antenna-based controller requires the rate of approach to a wall in addition to distance, e.g., in the form of a proportional-derivative (PD) controller. Neurophysiological experiments reveal that important features of the wall-following controller emerge at the earliest stages of sensory processing, namely in the antennal nerve. Furthermore, we embed the template in a robotic platform outfitted with a bio-inspired antenna. Using this system, we successfully test specific PD gains (up to a scale) fitted to the cockroach behavioral data in a "real-world" setting, lending further credence to the surprisingly simple notion that a cockroach might implement a PD controller for wall following. Finally, we embed the template in a simulated lateral-leg-spring (LLS) model using the center of pressure as the control input. Importantly, the same PD gains fitted to cockroach behavior also stabilize wall following for the LLS model. © 2008 IEEE.

Film bulk acoustic resonator pressure sensor with self temperature reference

A novel film bulk acoustic resonator (FBAR) with two resonant frequencies which have opposite reactions to temperature changes has been designed. The two resonant modes respond differently to changes in temperature and pressure, with the frequency shift being linearly correlated with temperature and pressure changes. By utilizing the FBAR's sealed back trench as a cavity, an on-chip single FBAR sensor suitable for measuring pressure and temperature simultaneously is proposed and demonstrated. The experimental results show that the pressure coefficient of frequency for the lower frequency peak of the FBAR sensors is approximately -17.4 ppm kPa-1, while that for the second peak is approximately -6.1 ppm kPa-1, both of them being much more sensitive than other existing pressure sensors. This dual mode on-chip pressure sensor is simple in structure and operation, can be fabricated at very low cost, and yet requires no specific package, therefore has great potential for applications. © 2012 IOP Publishing Ltd.

Wide Area Passive UHF RFID System using Antenna Diversity Combined with Phase and Frequency Hopping

This paper presents a long range and effectively error-free ultra high frequency (UHF) radio frequency identification (RFID) interrogation system. The system is based on a novel technique whereby two or more spatially separated transmit and receive antennas are used to enable greatly enhanced tag detection performance over longer distances using antenna diversity combined with frequency and phase hopping. The novel technique is first theoretically modelled using a Rician fading channel. It is shown that conventional RFID systems suffer from multi-path fading resulting in nulls in radio environments. We, for the first time, demonstrate that the nulls can be moved around by varying the phase and frequency of the interrogation signals in a multi-antenna system. As a result, much enhanced coverage can be achieved. A proof of principle prototype RFID system is built based on an Impinj R2000 transceiver. The demonstrator system shows that the new approach improves the tag detection accuracy from <50% to 100% and the tag backscatter signal strength by 10dB over a 20 m x 9 m area, compared with a conventional switched multi-antenna RFID system.

Demonstration of Improved Passive UHF RFID Coverage using Optically-Fed Distributed Multi-Antenna System

Optically-fed distributed antenna system (DAS) technology is combined with passive ultra high frequency (UHF) radio frequency identification (RFID). It is shown that RFID signals can be carried on directly modulated radio over fiber links without impacting their performance. It is also shown that a multi-antenna DAS can greatly reduce the number of nulls experienced by RFID in a complex radio environment, increasing the likelihood of successful tag detection. Consequently, optimization of the DAS reduces nulls further. We demonstrate RFID tag reading using a three antenna DAS system over a 20mx6m area, limited by building constraints, where 100% of the test points can be successfully read. The detected signal strength from the tag is also observed to increase by an average of approximately 10dB compared with a conventional switched multi-antenna RFID system. This improvement is achieved at +31dBm equivalent isotropically radiated power (EIRP) from all three antenna units (AUs).

RFID Tag Interrogation Systems

We describe an RFID tag reading system for reading one or more RFID Tags, the system comprising an RF transmitter and an RF receiver, a plurality of transmit/receive antennas coupled to said RF transmitter and to said RF receiver, to provide spatial transmit/receive signal diversity, and a tag signal decoder coupled to at least said RF receiver, wherein said system is configured to combine received RF signals from said antennas to provide a combined received RF signal, wherein said RF receiver has said combined received RF signal as an input; wherein said antennas are spaced apart from one another sufficiently for one said antenna not to be within the near field of another said antenna, wherein said system is configured to perform a tag inventory cycle comprising a plurality of tag read rounds to read said tags, a said tag read round comprising transmission of one or more RF tag interrogation signals simultaneously from said plurality of antennas and receiving a signal from one or more of said tags, a said tag read round having a set of time slots during which a said tag is able to transmit tag data including a tag ID for reception by said antenna, and wherein said system is configured to perform, during a said tag inventory cycle, one or both of: a change in a frequency of said tag interrogation signals transmitted simultaneously from said plurality of antennas, and a change in a relative phase of a said RF tag interrogation signals transmitted from one of said antennas with respect to another of said antennas.

Vibrations of coupled cylindrical-conical shells

The free vibrational characteristics of coupled conical-cylindrical shells is presented. The equations of motion for the cylindrical shell are solved using a wave approach while the equations of motion for the conical shells are solved using a power series solution. The use of both Donnell-Mushtari and Flügge equations of motion are investigated and their limitations are discussed. Results are presented in terms of natural frequencies for different boundary conditions and the purely torsional mode solution is described. The results from the analytical model presented are compared with those obtained from a finite element model solved with Nastran and other data available in literature.

Coupled thermal-magnetic analysis on thermally actuated superconducting flux pump

This paper presents numerical analysis of the thermally actuated superconducting flux pump. Visualization of the behavior of the magnetic flux helps our understanding of flux injection mechanism. In addition, in order to confirm validity of the result, we conducted a preliminary flux pump experiment. This result qualitatively agrees well with the experimental one. The flux pump system utilizes a particular behavior that permeability of some materials such as Gadolinium is sensitive to the temperature. In this paper a simple heater is used to control the flux pump system. © 2010 IEEE.

A Stochastic Model for Electron Multiplication Charge-Coupled Devices - From Theory to Practice

Electron multiplication charge-coupled devices (EMCCD) are widely used for photon counting experiments and measurements of low intensity light sources, and are extensively employed in biological fluorescence imaging applications. These devices have a complex statistical behaviour that is often not fully considered in the analysis of EMCCD data. Robust and optimal analysis of EMCCD images requires an understanding of their noise properties, in particular to exploit fully the advantages of Bayesian and maximum-likelihood analysis techniques, whose value is increasingly recognised in biological imaging for obtaining robust quantitative measurements from challenging data. To improve our own EMCCD analysis and as an effort to aid that of the wider bioimaging community, we present, explain and discuss a detailed physical model for EMCCD noise properties, giving a likelihood function for image counts in each pixel for a given incident intensity, and we explain how to measure the parameters for this model from various calibration images. © 2013 Hirsch et al.

State estimation schemes for independent component coupled hidden Markov models

Conventional Hidden Markov models generally consist of a Markov chain observed through a linear map corrupted by additive noise. This general class of model has enjoyed a huge and diverse range of applications, for example, speech processing, biomedical signal processing and more recently quantitative finance. However, a lesser known extension of this general class of model is the so-called Factorial Hidden Markov Model (FHMM). FHMMs also have diverse applications, notably in machine learning, artificial intelligence and speech recognition [13, 17]. FHMMs extend the usual class of HMMs, by supposing the partially observed state process is a finite collection of distinct Markov chains, either statistically independent or dependent. There is also considerable current activity in applying collections of partially observed Markov chains to complex action recognition problems, see, for example, [6]. In this article we consider the Maximum Likelihood (ML) parameter estimation problem for FHMMs. Much of the extant literature concerning this problem presents parameter estimation schemes based on full data log-likelihood EM algorithms. This approach can be slow to converge and often imposes heavy demands on computer memory. The latter point is particularly relevant for the class of FHMMs where state space dimensions are relatively large. The contribution in this article is to develop new recursive formulae for a filter-based EM algorithm that can be implemented online. Our new formulae are equivalent ML estimators, however, these formulae are purely recursive and so, significantly reduce numerical complexity and memory requirements. A computer simulation is included to demonstrate the performance of our results. © Taylor & Francis Group, LLC.

Distribution matching for transduction

Many transductive inference algorithms assume that distributions over training and test estimates should be related, e.g. by providing a large margin of separation on both sets. We use this idea to design a transduction algorithm which can be used without modification for classification, regression, and structured estimation. At its heart we exploit the fact that for a good learner the distributions over the outputs on training and test sets should match. This is a classical two-sample problem which can be solved efficiently in its most general form by using distance measures in Hilbert Space. It turns out that a number of existing heuristics can be viewed as special cases of our approach.