Signal Processing Components Research Articles

DSP-based New On-line Dead Time Compensation Strategy of a PMSM Drive through Digital Signal Processing and Harmonic Component Extraction for a Robot Arm Application

DSP-based New On-line Dead Time Compensation Strategy of a PMSM Drive through Digital Signal Processing and Harmonic Component Extraction for a Robot Arm Application

Improved estimation scheme for disturbance due to dead time and inverter nonlinearity in inverter‐fed PMSM drive

An improved estimation scheme for disturbance due to the dead time and inverter nonlinearity in an inverter-fed permanent magnet synchronous motor (PMSM) drive is presented. The proposed scheme is based on a signal processing and harmonic component extraction and does not require any additional circuits nor parameter information. Furthermore, it is faster to estimate the disturbance as compared with the conventional method based on harmonic analysis. The effectiveness of the proposed scheme is verified through comparative simulations.

Wireless Medical-Embedded Systems: A Review of Signal-Processing Techniques for Classification

Body-worn sensor systems will help to revolutionize the medical field by providing a source of continuously collected patient data. This data can be used to develop and track plans for improving health (more sleep and exercise), detect disease early, and provide an alert for dangerous events (e.g., falls and heart attacks). The amount of data collected by even a small set of sensors running all day is too much for any person to analyze. Signal processing and classification can be used to automatically extract useful information. This paper presents a general classification framework for wireless medical devices and reviews the available literature for signal processing and classification systems or components used in body-worn sensor systems. Examples focus on electrocardiography classification and signal processing for inertial sensors.

HEARING APPARATUS COMPRISING A MEMBRANE ON THE BATTERY COMPARTMENT INTERIOR

A hearing apparatus with a housing including a housing interior is provided. Signal processing components are accommodated in the housing interior. The hearing apparatus includes a battery compartment fastened in or on the housing, which has a battery compartment interior into which a battery is inserted for supplying power to the hearing apparatus. Further, a membrane is provided, which separates the housing interior from the battery compartment interior. The membrane is fastened to the housing or to the battery compartment.

HEARING APPARATUS CHIP WITH A SEPARATE EMC GROUND AND CORRESPONDING HEARING APPARATUS

In the English translation document, please replace the abstract with the following: A Hearing apparatuses and a hearing apparatus chip are provided. A hearing apparatus chip for processing a signal of a hearing apparatus includes a signal-processing component and a first ground wire connected to a first terminal of the component. The signal processing component includes a second ground wire galvanically separated from the first ground wire on the chip and is connected to a second terminal of the component by way of a capacitor, in order to conduct interference signals as a result of electromagnetic couplings. In particular, the sensitive ground of a preamplifier is not then interfered with by leakage currents.

兰州重离子加速器控制系统DSP组件设计

兰州重离子加速器控制系统DSP组件设计

Combined multiuser signal classification and blind equalization

A multiuser automatic modulation classifier (MAMC) is an important signal processing component of a multiantenna cognitive radio (CR) receiver that helps the radio in identifying modulation format employed by multiple users in a frequency band simultaneously. In a typical wireless communication, transmitted signals are subjected to multipath fading and interference from other users. Multipath fading not only affects symbol detection performance but also affects the performance of the automatic modulation classifier. A multi input multi output (MIMO) blind equalizer is another important component of a multiantenna CR receiver that improves symbol detection performance by reducing inter symbol interference and inter user interference. In a CR scenario it is preferable to consider the performance of the AMC also while adapting the parameters of the blind equalizer. In this paper we propose MIMO blind equalizers that improves the performance of both multiuser symbol detection and cumulants based MAMC. Computer simulations are provided to illustrate this concept and the proposed algorithm.

Tailored hybrid hyperbranched polyglycidol-silica nanocomposites with high third-order nonlinearity

Abstract One of the most convenient techniques for optical material fabrication is the sol–gel processing. It can be performed at low temperature that enables one to entrap even relatively unstable organic substances into silica matrix at the nanometer scale, thus developing homogeneous hybrid organic–inorganic nanocomposite materials of various functionalities. Here, novel hybrid organic–inorganic nanocomposites with good optical transparency and high third-order nonlinearity were prepared biomimetically through the mineralization of dendritic macromolecules (hyperbranched polyglycidols) using a compatible ethylene glycol-containing silica precursor. The synthesis was performed at neutral pH media in aqueous solutions without addition of organic solvents at ambient conditions owing to the catalysis of processing. Polyglycidols provided also the formation of gold nanoparticles localized in their core. They served as reducing and stabilizing agents. It is shown that trace amounts of nanoparticles could regulate nonlinear properties of a nanocomposite. High nonlinearity manifests itself in a supercontinuum generation at remarkably short lengths ca. 1 mm. The phenomenon consists of filamentous intense white lighting due to the spectral broadening of initial ultrashort (femtosecond) laser pulses propagating through the material. The developed hybrid nanocomposites possessing large nonlinearity, high-speed optical response, stability under intense lighting, low-cost, and easy preparation are promising for a diverse range of applications as active components for all-optical signal processing from chemical sensing to biological cell imaging and lighting control in telecommunication.

Nanophotonics Based on Semiconductor-Photonic Crystal/Quantum Dot and Metal-/Semiconductor-Plasmonics

This paper reviews our recent activities on nanophotonics based on a photonic crystal (PC)/quantum dot (QD)-combined structure for an all-optical device and a metal/semiconductor composite structure using surface plasmon (SP) and negative refractive index material (NIM). The former structure contributes to an ultrafast signal processing component by virtue of new PC design and QD selective-area-growth technologies, while the latter provides a new RGB color filter with a high precision and optical beam-steering device with a wide steering angle.

Identification of exonic regions in DNA sequences using cross-correlation and noise suppression by discrete wavelet transform

BackgroundThe identification of protein coding regions (exons) in DNA sequences using signal processing techniques is an important component of bioinformatics and biological signal processing. In this paper, a new method is presented for the identification of exonic regions in DNA sequences. This method is based on the cross-correlation technique that can identify periodic regions in DNA sequences.ResultsThe method reduces the dependency of window length on identification accuracy. The proposed algorithm is applied to different eukaryotic datasets and the output results are compared with those of other established methods. The proposed method increased the accuracy of exon detection by 4% to 41% relative to the most common digital signal processing methods for exon prediction.ConclusionsWe demonstrated that periodic signals can be estimated using cross-correlation. In addition, discrete wavelet transform (DWT) can minimise noise while maintaining the signal. The proposed algorithm, which combines cross-correlation and DWT, significantly increases the accuracy of exonic region identification.

An L 1-regularized logistic model for detecting short-term neuronal interactions

Interactions among neurons are a key component of neural signal processing. Rich neural data sets potentially containing evidence of interactions can now be collected readily in the laboratory, but existing analysis methods are often not sufficiently sensitive and specific to reveal these interactions. Generalized linear models offer a platform for analyzing multi-electrode recordings of neuronal spike train data. Here we suggest an L(1)-regularized logistic regression model (L(1)L method) to detect short-term (order of 3 ms) neuronal interactions. We estimate the parameters in this model using a coordinate descent algorithm, and determine the optimal tuning parameter using a Bayesian Information Criterion. Simulation studies show that in general the L(1)L method has better sensitivities and specificities than those of the traditional shuffle-corrected cross-correlogram (covariogram) method. The L(1)L method is able to detect excitatory interactions with both high sensitivity and specificity with reasonably large recordings, even when the magnitude of the interactions is small; similar results hold for inhibition given sufficiently high baseline firing rates. Our study also suggests that the false positives can be further removed by thresholding, because their magnitudes are typically smaller than true interactions. Simulations also show that the L(1)L method is somewhat robust to partially observed networks. We apply the method to multi-electrode recordings collected in the monkey dorsal premotor cortex (PMd) while the animal prepares to make reaching arm movements. The results show that some neurons interact differently depending on task conditions. The stronger interactions detected with our L(1)L method were also visible using the covariogram method.

Robust automatic modulation classification and blind equalization: novel cognitive receivers

The automatic modulation classifier (AMC) is an important signal processing component that helps the cognitive radio (CR) better utilize the spectrum. In a typical CR scenario, training sequence or channel knowledge is not available, and hence blind equalizers are widely used. The multipath fading channel not only affects symbol detection performance but also affects the performance of the AMC. In a conventional single input single output blind equalizer, the weights of the equalizer are adapted by minimizing cost functions that are non quadratic (multimodal). Convergence of the blind equalizer to a local minimum affects both symbol detection performance and AMC performance. In a CR scenario, it is preferable to consider the performance of the AMC also while adapting the blind equalizer weights. In this article, we propose novel CR receivers where the performance of the AMC is also considered while adapting the parameters of the blind equalizer. Computer simulations are given to illustrate the concept and yield promising results.

Modulation of rod photoreceptor output by HCN1 channels is essential for regular mesopic cone vision

Retinal photoreceptors permit visual perception over a wide range of lighting conditions. Rods work best in dim, and cones in bright environments, with considerable functional overlap at intermediate (mesopic) light levels. At many sites in the outer and inner retina where rod and cone signals interact, gap junctions, particularly those containing Connexin36, have been identified. However, little is known about the dynamic processes associated with the convergence of rod and cone system signals into ON- and OFF-pathways. Here we show that proper cone vision under mesopic conditions requires rapid adaptational feedback modulation of rod output via hyperpolarization-activated and cyclic nucleotide-gated channels 1. When these channels are absent, sustained rod responses following bright light exposure saturate the retinal network, resulting in a loss of downstream cone signalling. By specific genetic and pharmacological ablation of key signal processing components, regular cone signalling can be restored, thereby identifying the sites involved in functional rod-cone interactions.

An Analysis of Speech Recognition Performance Based Upon Network Layers and Transfer Functions

Speech is the most natural way of information exchange. It provides an efficient means of means of manmachine communication using speech interfacing. Speech interfacing involves speech synthesis and speech recognition. Speech recognition allows a computer to identify the words that a person speaks to a microphone or telephone. The two main components, normally used in speech recognition, are signal processing component at front-end and pattern matching component at back-end. In this paper, a setup that uses Mel frequency cepstral coefficients at front-end and artificial neural networks at back-end has been developed to perform the experiments for analyzing the speech recognition performance. Various experiments have been performed by varying the number of layers and type of network transfer function, which helps in deciding the network architecture to be used for acoustic modelling at back end.

Fluorescent Protein-Based Redox Probes

Redox biochemistry is increasingly recognized as an integral component of cellular signal processing and cell fate decision making. Unfortunately, our capabilities to observe and measure clearly defined redox processes in the natural context of living cells, tissues, or organisms are woefully limited. The most advanced and promising tools for specific, quantitative, dynamic and compartment-specific observations are genetically encoded redox probes derived from green fluorescent protein (GFP). Within only few years from their initial introduction, redox-sensitive yellow FP (rxYFP), redox-sensitive GFPs (roGFPs), and HyPer have generated enormous interest in applying these novel tools to monitor dynamic redox changes in vivo. As genetically encoded probes, these biosensors can be specifically targeted to different subcellular locations. A critical advantage of roGFPs and HyPer is their ratiometric fluorogenic behavior. Moreover, the probe scaffold of redox-sensitive fluorescent proteins (rxYFP and roGFPs) is amenable to molecular engineering, offering fascinating prospects for further developments. In particular, the engineering of redox relays between roGFPs and redox enzymes allows control of probe specificity and enhancement of sensitivity. Genetically encoded redox probes enable the functional analysis of individual proteins in cellular redox homeostasis. In addition, redox biosensor transgenic model organisms offer extended opportunities for dynamic in vivo imaging of redox processes.

All-Optical Clocked Flip-Flops and Binary Counting Operation Using SOA-Based SR Latch and Logic Gates

All-optical digital devices are key components for advanced signal processing in next generation optical networks and optical computing. In most digital systems, photonic integrated circuits are required to carry out high-speed energy efficient functionalities. In this paper, an entire set of integrable all-optical clocked flip-flops and an all-optical binary counter are proposed, as applications of SR latches and logic gates previously introduced in literature. The SR latch is based on gain quenching mechanism between two coupled ring lasers using a semiconductor optical amplifier (SOA) as active element. Photonic logic functions are carried out by exploiting four wave mixing (FWM) and cross gain modulation (XGM) nonlinear effects in SOAs. Different flip-flop logical functionalities, including SR-, D-, T-, and JK-types, as well as an all-optical binary counter, are obtained by adding one of the logic gates, or a combination of them, to the latch scheme. The effectiveness of the proposed schemes is demonstrated by extinction ratio and Q-factor measurements. All solutions are tunable in the whole C-band and can work at different counting rate without any reconfiguration. Photonic integration allows to increase the functioning rate beyond gigahertz and reduce the switching energy.

Device variability and circuit redundancy in signal processing based on nanoswitches

Signal processing based on molecular switches whose conductance can be tuned by anexternal stimulus between two (on and off) states has been proposed recently(Cervera et al 2008 J. Appl. Phys. 104 084317). The basic building block is a metalnanoparticle linked to two electrodes by an organic ligand and a nanoswitch. Thenet charge delivered by this nanostructure exhibits a sharp resonance when thealternating potential applied between the electrodes has the same frequency as theperiodic variation between the on and off conductance states induced on thenanoswitch. This resonance can be used to process an external signal by selectivelyextracting the weight of the different harmonics. However, because of the fabricationprocess at the nanoscale, the nanostructures will show a significant variability inthe physical characteristics. By using a phenomenological model that includesthis variability, the stochastic nature of electron transference, and the thermalnoise, we demonstrate that reliable signal processing can still be achieved byadapting the number of nanoswitches per bit of information (circuit redundancy) tothe nanostructure tolerance (device variability). Extensive kinetic Monte Carlosimulations show that a moderate level of redundancy can compensate for significantnanostructure variability. This result gives support to the concept of ensembles ofredundant switches as reliable components for signal processing at the nanoscale.

Electronic depth control with Neuroprobes microarrays

Event Abstract Back to Event Electronic depth control with Neuroprobes microarrays Balázs Dombóvári1, 2*, Richard Csercsa1, Karsten Seidl3, Patrick Ruther3, Herc Neves4 and Istvan Ulbert1, 2 1 Institute for Psychology, Hungarian Academy of Sciences, Hungary 2 Peter Pazmany Catholic University, Hungary 3 Department of Microsyst. Engineering (IMTEK), University of Freiburg, Germany 4 Interuniversitair Microelektronica Centrum, Belgium We have developed electronic depth control software for managing intracortical microprobes designed by the Neuroprobes consortium for in vivo extracellular recording of neurons. The microprobe arrays contain a large number (up to 8208) of electronically switchable electrodes to enable the precise positioning of each electrode contacts with respect to individual neurons. Recorded signal quality may degrade over time due to tissue drift, cell expiration, inflammation and reactive gliosis among others. Hence, there is a need for (re)selecting the electrodes which are most informative about the firing activities of the cells. In our case, we don’t move the array mechanically, but using electronics to select the ‘best’ electrodes for recording along each shaft, based upon a signal quality metric. In the software there are two different methods to select the electrodes. Either, the user directly selects the electrodes manually, or starts an additional signal quality scan to give assistance in the electrode selection (semi-automatic mode). In the latter case results of the signal to noise computations are visualized by color-coding. The software is suitable for manipulating all versions of Neuroprobes microarrays (2mm, 4mm, 8mm length). Finally, the selection is sent to the hardware controller by a defined protocol. In addition the software provides a graphical user interface and integrates the components for data acquisition, signal processing, and communication with the hardware controllers and for storing the neural signals for further analysis. Conference: 12th Meeting of the Hungarian Neuroscience Society, Budapest, Hungary, 22 Jan - 24 Jan, 2009. Presentation Type: Poster Presentation Topic: Developmental neurobiology and subcortical functions Citation: Dombóvári B, Csercsa R, Seidl K, Ruther P, Neves H and Ulbert I (2009). Electronic depth control with Neuroprobes microarrays. Front. Syst. Neurosci. Conference Abstract: 12th Meeting of the Hungarian Neuroscience Society. doi: 10.3389/conf.neuro.01.2009.04.050 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 27 Feb 2009; Published Online: 27 Feb 2009. * Correspondence: Balázs Dombóvári, Institute for Psychology, Hungarian Academy of Sciences, Budapest, Hungary, dombovari@cogpsyphy.hu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Balázs Dombóvári Richard Csercsa Karsten Seidl Patrick Ruther Herc Neves Istvan Ulbert Google Balázs Dombóvári Richard Csercsa Karsten Seidl Patrick Ruther Herc Neves Istvan Ulbert Google Scholar Balázs Dombóvári Richard Csercsa Karsten Seidl Patrick Ruther Herc Neves Istvan Ulbert PubMed Balázs Dombóvári Richard Csercsa Karsten Seidl Patrick Ruther Herc Neves Istvan Ulbert Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Nonlinear plasmonics: controlling light with light

Many scientists believe that the future of signal processing and computing lies not within electronics but in the field of subwavelength optics. Controlling light at sub-wavelength scales, forbidden by traditional far-field optics, relies on surface plasmon techniques. Surface plasmon polaritons (SPPs) are electromagnetic waves that exist on the surface of metals such as gold or silver. The interaction between the electromagnetic field and the free electrons in the metal helps confine SPPs tightly to the surface. The behavior of this wave can bemanipulated by nanostructuring either the surface or a nearby dielectric. By contrast, metallic particles (or nanoscale dielectric voids in ametallic host) can enhance the field by supporting localized plasmonic excitations that create superior field confinement. Both mechanisms can locally control the electromagnetic field, a pre-requisite for the development of such light-based circuitry and devices. Researchers have used plasmonics to design and test various circuit elements such as waveguides, mirrors, lenses, and resonators based on nanostructured metal films.1 These passive plasmonic systems can provide some of the essential components for signal processing and optical circuitry, but creating optical analogs to electrical circuits requires active devices. In order to directly make plasmonic components, scientists commonly propose two approaches, both based on themodification of the refractive index near the metal surface. The first uses the electro-optic effect exhibited, for example, by liquid crystal molecules. Here, the refractive index depends on the molecular alignment, which can be modulated using an electric field. Hybrid electro-optic devices are promising since electronic and photonic signals can be transferred, processed, and interconnected in the same metallic circuitry. A second method relies on dielectric materials with a large Kerr nonlinearity, or a refractive index that depends on the intensity of the illuminating light. Figure 1. (left) Modulation of transmission by an array of gold nanorods (perpendicular to the substrate) and (right) a hole array in a thin gold film. Both were coated with poly-3BCMU (blue in schematic) and pumped with control light at 514nm.

Suitability of a PXI platform for an electrical impedance tomography system

There are many different electrical impedance tomography (EIT) systems which are either non-commercial (in-house products) or commercial products. However, these systems are usually designed for specific applications and therefore the functionality of the systems might be limited. Nowadays there are commercially available many low-cost, efficient and accurate multifunctional components for data acquisition and signal processing. Therefore, it should be possible to construct an EIT system which is mainly built from commercially available components. The main goal of this work was to study the performance of a PXI-based EIT systemPCI eXtension for Instrumentation.. In this work, a PXI-based EIT system with 16 independent current injection channels and 80 independent measurement channels was constructed and tested. The results indicate that an EIT system can be constructed using a PXI platform which decreases the construction time of the system. Moreover, the system is efficient, accurate, modular, and it is not limited to any predetermined measurement protocols.