Real-time Processing Algorithms Research Articles

Development of a Real-Time Pulse Processing Algorithm for TES-Based X-Ray Microcalorimeters

We report here a real-time pulse processing algorithm for superconducting transition-edge sensor (TES) based x-ray microcalorimeters. TES-based microcalorimeters offer ultra-high energy resolutions, but the small volume of each pixel requires that large arrays of identical microcalorimeter pixels be built to achieve sufficient detection efficiency. That in turn requires as much pulse processing as possible must be performed at the front end of readout electronics to avoid transferring large amounts of data to a host computer for post-processing. Therefore, a real-time pulse processing algorithm that not only can be implemented in the readout electronics but also achieve satisfactory energy resolutions is desired. We have developed an algorithm that can be easily implemented in hardware. We then tested the algorithm offline using several data sets acquired with an 8 × 8 Goddard TES x-ray calorimeter array and 2 ×16 NIST time-division SQUID multiplexer. We obtained an average energy resolution of close to 3.0 eV at 6 keV for the multiplexed pixels while preserving over 99% of the events in the data sets.

Real-Time Simplex Growing Algorithms for Hyperspectral Endmember Extraction

The simplex growing algorithm (SGA) was recently developed as an alternative to the N-finder algorithm (N-FINDR) and shown to be a promising endmember extraction technique. This paper further extends the SGA to a versatile real-time (RT) processing algorithm, referred to as RT SGA, which can effectively address the following four major issues arising in the practical implementation for N-FINDR: (1) use of random initial endmembers which causes inconsistent final results; (2) high computational complexity which results from an exhaustive search for finding all endmembers simultaneously; (3) requirement of dimensionality reduction because of large data volumes; and (4) lack of RT capability. In addition to the aforementioned advantages, the proposed RT SGA can also be implemented by various criteria in endmember extraction other than the maximum simplex volume.

Real-Time Query Processing for Sensor Networks Based on Ant Algorithm

无线传感器网络因不同应用而被广泛部署于各种场合,通常被视为分布式数据库.可以通过向该类数据库发布查询请求来获取事件相关的响应信息.一些具有实时需求的应用对查询时延要求较高,而目前存在的查询算法通常不能很好地满足实时查询应用的需求.针对此类特定应用,提出了基于蚁群优化的实时查询处理算法,该算法采用基于事件重要性的分环存储策略和基于蚁群算法的分布式搜索机制,充分利用蚁群优化算法的自组织和正反馈等特征,综合提高查询处理算法的节能性、实时性及查询请求接受率,为分布式动态并行实时查询应用提供新的思路.执行过程仅需局;Wireless sensor networks are often deployed in diverse application specific contexts, which can be treated essentially as distributed databases. The event-involved responses can be obtained by issuing queries to this kind of database. The applications with real-time requirement have tight constraints on query delay. However, the existing query algorithms cannot meet the demands of the real-time query applications. With regard to the special applications, a real-time query processing algorithm based on ant colony optimization is proposed. In this algorithm,priority-based multiple-rings storage scheme and ant-based distributed search mechanism are adopted to improve the integrated performance of energy-efficiency, delay and query reception rate. It takes advantage of the self-organization and positive feedback characteristics of ant colony optimization algorithm. The proposed algorithm provide a new idea for distributed dynamic parallel real-time query applications, demanding merely local information to obtain named events efficiently and determine the number and allocation of event replicas adaptively.Theoretical analysis and experiments prove that compared with other existing query algorithms, this algorithm cannot only improve the performance of energy-efficiency and reception, it can also shorten the query delay considerably.

Optimality and Improvement of Dynamic Voltage Scaling Algorithms for Multimedia Applications

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The high complexity and time-varying workload of emerging multimedia applications poses a major challenge for dynamic voltage scaling (DVS) algorithms. Although many DVS algorithms have been proposed for real-time applications, an efficient method for evaluating the optimality of such DVS algorithms for multimedia applications does not yet exist. In this paper, we propose the first offline linear programming (LP) method to determine the minimum energy consumption for processing multimedia tasks under stringent delay deadlines. On the basis of the obtained energy lower bound, we evaluate the optimality of various existing DVS algorithms. Furthermore, we extend the LP formulation in order to construct an online DVS algorithm for real-time multimedia processing based on robust sequential linear programming. Simulation results obtained by decoding a wide range of video sequences show that, on average, our online algorithm provides a scheduling solution that requires less than 0.3% more energy than the optimal lower bound with only 0.03% miss rate. In comparison, a very recent algorithm consumes approximately 4% more energy than the optimal lower bound at the same miss rate. </para>

Real-time N-finder processing algorithms for hyperspectral imagery

N-finder algorithm (N-FINDR) is probably one of most popular and widely used algorithms for endmember extraction in hyperspectral imagery. When it comes to practical implementation, four major obstacles need to be overcome. One is the number of endmembers which must be known a priori. A second one is the use of random initial endmembers to initialize N-FINDR, which generally results in different sets of final extracted endmembers. Consequently, the results are inconsistent and not reproducible. A third one is requirement of dimensionality reduction (DR) where different used DR techniques produce different results. Finally yet importantly, it is the very expensive computational cost caused by an exhaustive search for endmembers all together simultaneously. This paper re-designs N-FINDR in a real time processing fashion to cope with these issues. Four versions of Real Time (RT) N-FINDR are developed, RT Iterative N-FINDR (RT IN-FINDR), RT SeQuential N-FINDR (RT SQ N-FINDR), RT Circular N-FINDR, RT SuCcessive N-FINDR (RT SC N-FINDR), each of which has its own merit for implementation. Experimental results demonstrate that real time processing algorithms perform as well as their counterparts with no real-time processing.

Image and video processing on FPGAs: An Exploration Framework for Real-Time Applications

This work presents a design framework for real-time image and video processing enabling exploration and evaluation of different processing techniques. The goal of our educational approach is to develop a flexible and easily customizable environment for prototyping different processing techniques on Field Programmable Gate Arrays (FPGAs), targeting specific applications. In this paper we give an overview of different requirements and techniques of video processing featuring FPGAs. Three real-time video processing algorithms were combined to show the advantages and characteristics of our approach. Within the framework, the modules running in parallel can be easily swapped at run-time according to the application specific needs.

A Real-time Multiview Video Coding System using Fast Disparity Estimation

In this paper, a real-time multiview video coding system using fast disparity estimation is proposed, In the multiview encoder, adaptive disparity-motion estimation (DME) for an effective 3-dimensional (3D) processing are proposed, That is, by adaptively predicting the mutual correlation between stereo images in the key-frame using the proposed algorithm, the bandwidth of stereo input images can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and adaptive disparity vectors. Also, in multiview decoder, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (DSA) for real-time multiview video processing is proposed, The proposed IVR can reduce a processing time of disparity estimation by selecting adaptively disparity search range. Accordingly, the proposed multiview video coding system is able to increase the efficiency of the coding rate and improve the resolution.

Electromagnetic Compatibility of the Military Handset with Hidden Authorization Function Based on MIL-STD-461D Results

In this paper we present algorithm and hardware architecture of the new military communication device dedicated for VHF battlefleld radio stations. The results of the compati- bility tests carried out for this device according to the norm MIL-STD-461D are also presented together with the flgures and comments. Measurements were carried out at the Electromagnetic Compatibility Laboratory, Faculty of Electronics, Military University of Technology. The Lab- oratory have accreditation given by the Polish Centre for Accreditation for carrying out those military devices measurements. Described results of measurements will be a base for introduction this developed device into the Polish Armed Forces equipment. One of the most important security problems unsolved till this time in the communications links is voice authorization of the telephone or radio subscriber. Problem is more obvious when it is considered both current voice communications over digital and analog channels: VoIP, PSTN, GSM and state-of-the-art real-time, artiflcial, speech synthesis in the context of potential risk of impersonating, known in information technology as a Presented algorithm and hardware architecture are the proposals for increasing security level in unprotected voice calls, as a response to a new telephone attacks named \voice spooflng. At present, subscriber's authorization in telephone calls is performed in the most cases in sub- jective way using our Human Auditory System. Well known scheme of subjective authorization is based on knowledge of dedicated speciflc person's voice. New scheme of the authorization is based on objective way using watermarking (data hiding) technology. Additional binary signature as a inaudible watermark is embedded in the host's signal voice in the radio or telephone handset and then transmitted over communications links. At the receiving side, using dedicated hardware based on real-time processing algorithm, watermark is extracted and binary signature is compared with the set of binary signatures storage in the handset's memory. Results of the authorization process is displayed on handset's LCD. Hardware architecture of the handset is based on the fast, ∞oating- point Digital Signal Processor TMS320C6713 and microcontroller ARM7TDMI family. Handset transmits, watermarked, analog voice, using standard voice interface in the TRC9200 battlefleld VHF PR4G radio station family.

Automatic nanohandling station inside a scanning electron microscope

Current research work on the development of automated nanohandling systems in a scanning electron microscope (SEM) is presented. Two experimental set-ups are shown in which nanohandling robots operate in the vacuum chamber of an SEM. A client—server control system that can integrate various microrobots and sensors has been developed and evaluated by automatic handling of TEM (transmission electron microscope) lamellae by two nanorobots. The robots are controlled in a closed-loop way by using images from several CCD (charge coupled device) cameras and from the SEM. Algorithms for real-time processing of noisy SEM images have been implemented and tested. The experiment on automatic handling of TEM lamellae inside an SEM is described. The other set-up contains a nanohandling robot using the probe of an atomic force microscope (AFM) as end-effector. The manipulation of individual multiwall carbon nanotubes (MWNTs) and the characterization of nanofilms by nanoindentation are the applications being investigated. The experimental set-up includes a nanopositioning piezo stage with three degrees of freedom (DoF) and a three-axis nanomanipulator. Piezoresistive AFM probes are applied as end-effectors. In this way the acting forces can be detected, allowing force feedback for the station's control system. First investigations have been carried out by bending MWNTs and calculating their elastic modulus.

ATCA data acquisition system for gamma-ray spectrometry

The gamma-ray spectrometer JET EP2 (Joint European Torus enhancement project 2) project aims to perform high-resolution gamma spectroscopy at very high count rate (up to few MHz). Traditional analogue electronic has count rate and pulse processing limitations (long dead-time, pile-up challenge). Digital pulse processing (DPP) systems have been shown to have better performance than analogue ones for processing neutrons or/and gamma-ray signals. DPP can synthesize almost any pulse response shape without the signal degradation associated to complex analogue paths. High-speed transient recorders (TR) with auto-trigger functionality are used to digitize and store the detailed shape of pulses. The data acquisition (DAQ) system provides sophisticated analysis/data reduction based on real time algorithms, implemented in field programmable gate arrays (FPGA), for Pulse Height Analysis (PHA) while resolving pulse pile-up of digitized pulses. This paper describes a new DAQ system for real-time pulse analysis. The system is based on the Advanced Telecommunications Computing Architecture™ (ATCA™) and contains an ix86-based processor blade with up to 40 GFLOPS and a TR module interconnected through PCI Express (PCIe) links. TR module features: (i) 8 channels of 13 bit resolution with accuracy equal or higher than 11 bit to cope with the expected signal-to-noise ratio (SNR) of the input pulses; (ii) up to 500 MSamples/s sampling rate with the possibility to achieve 1 GSamples/s; and (iii) 2 or 4 GB of local memory. The core of the TR module is two FPGAs able to perform real-time processing algorithms such as PHA and pile-up resolution. This will allow data reduction by a factor of at least 6 and eventually spectra output in real-time.

Development and control of a versatile nanohandling robot cell

Current research work on the development of a nanohandling robot cell in a scanning electron microscope (SEM) is presented. An experimental setup is shown, in which two microrobots cooperate in the vacuum chamber of an SEM. One microrobot is used as manipulator of the tool and a second one is used for manipulating the object. Priority objective in future is the systematic prototyping of CNT-based nanodevices. Special algorithms for real-time processing of noisy SEM images have been implemented and tested. In addition, a 3D graphical user interface has been developed and delivers depth information which is often crucial for teleoperation of nanoobjects due to the lack of depth information in original SEM images. In order to enable automated nanohandling, a new control strategy is proposed. One key challenge for a successful automation is continuous pose estimation of tool and object which can be solved by applying the developed 2D and 3D tracking algorithms. The functionality of the robot cell is exemplified by handling and mechanical characterization of carbon nanotubes (CNTs).

Data acquisition ATCA system for neutron and gamma-rays spectrometries

Digital pulse processing (DPP) systems are known to have better performance than analog ones for neutron and/or gamma-ray pulses. DPP can synthesize almost any pulse response shape without the associated signal degradation which happens in a complex analog path. Measuring techniques involving detectors/spectrometers for fusion diagnostics rely on real-time algorithms, implemented in field programmable gate array (FPGA), for pulse height analysis, pulse shape discrimination, and pileup rejection of digitized pulses in real time for reduced data throughput, monitoring, and control. This article describes a data acquisition system for real-time pulse analysis based on ATCA and contains a 6 GFLPOS i×86-based control unit and a number of transient recorder (TR) modules interconnected through PCI Express links. Each TR module features (i) eight channels of 12bit resolution with accuracy equal or higher than 10bits, (ii) 200Msamples∕s of sampling rate achieving 400Msamples∕s in an interleaved architecture, (iii) 2 or 4Gbytes of local memory, and (iv) two field FPGAs able to perform real-time processing algorithms.

DEVELOPMENT AND CONTROL OF A VERSATILE NANOHANDLING ROBOT CELL

Current research work on the development of a nanohandling cell in a scanning electron microscope (SEM) is presented. An experimental setup is shown, in which two microrobots cooperate in the vacuum chamber of an SEM. One microrobot is used as manipulator and a second one is used as sample holder. The task to be carried out is gripping of carbon nanotubes (CNT). In order to enable automatic gripping an automation strategy is introduced. One key challenge for a successful automation is the continuous pose estimation of the gripper and the CNT. Therefore, algorithms for real-time processing of noisy SEM images have been implemented and tested.

AN INSTANTANEOUS AMBIGUITY RESOLUTION PROCEDURE SUITABLE FOR MEDIUM-SCALE GPS REFERENCE STATION NETWORKS

There is a trend for the establishment of regional-scale GPS permanent receiver networks, for a variety of appli- cations including support of high accuracy, carrier phase- based positioning for surveying and precise navigation. When implemented in real-time, GPS users located within the region enclosed by multiple GPS reference sta- tions can precisely position by using, for example, the 'correction terms' generated and transmitted by the refer- ence station network. For such a configuration one of the major challenges is that the integer ambiguities have to be resolved during the real-time processing of the refer- ence network data in order to ensure the generation of the carrier phase corrections, even when the reference receiv- ers are many tens of kilometers apart. Due to the pres- ence of distance dependent errors in the double- differenced data (principally the ionospheric and tropo- spheric delays) reliable instantaneous (single epoch) am- biguity resolution is difficult in the case of medium-scale reference networks (defined here as where the reference stations are typically in the range 50-100km apart). In practice the ambiguities between the reference stations could be correctly fixed during some sort of 'initializa- tion' procedure. However, the main challenge is to keep on fixing ambiguities instantaneously (or with minimum delay) when a satellite experiences cycle-slips, a long data gap, or when a new satellite rises above the horizon. In this paper, a three-step strategy is proposed for over- coming these challenges which is suitable for implemen- tation in real-time. In the first step the high correlation of the atmospheric delay between adjacent epochs is used to assist the cycle-slip recovery and ambiguity resolution. Then these atmosphere models are used in a predictive manner in the double-differenced observations, on an ep- och-by-epoch and satellite-by-satellite basis. Finally, these atmosphere models are applied in a real-time kine- matic data processing algorithm to fix the ambiguities during situations when there is a long data gap, or when a new satellite rises between the reference stations. Test data from GPS reference stations spaced 80km apart were used to evaluate the algorithm. The results indicate that the proposed algorithm can provide reliable integer ambiguities, very quickly, in the case of medium-scale reference networks.

Audio signal processing by neural networks

In this paper a review of architectures suitable for nonlinear real-time audio signal processing is presented. The computational and structural complexity of neural networks (NNs) represent in fact, the main drawbacks that can hinder many practical NNs multimedia applications. In particular efficient neural architectures and their learning algorithm for real-time on-line audio processing are discussed. Moreover, applications in the fields of (1) audio signal recovery, (2) speech quality enhancement, (3) nonlinear transducer linearization, (4) learning based pseudo-physical sound synthesis, are briefly presented and discussed.

RFImitigation methods in radio astronomy

Various methods of radio frequency interference (RFI) mitigation methods at radio astronomy tele- scopes are being considered. Special attention is given to real-time processing algorithms. Computer simulations and observational results are used to describe the applicability of these methods. Best results can be achieved when the RFI mitigation procedures are adapted to the particular radio telescope, the type of observations, and the peculiarities of the RFI environment. A combination of dierent linear and non-linear methods in the tem- poral and frequency domains, with and without the use of reference antennas, may give considerable suppression of strong RFI.

Real-Time Interactive Self-Modeling Mixture Analysis

A modified algorithm of SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) has been developed to build models in real time from ion mobility spectrometry (IMS) data. A real-time LabVIEW virtual instrument (VI) has been developed to continuously acquire data and simultaneously extract spectra and concentration profiles. The concentration profiles indicate changes of the individual component concentrations in the instrument response with respect to sample acquisition time, and the spectra indicate the characteristic peaks of the components with respect to the ion mobility. This display allows subtle changes in the instrument's response and the complete measurement history to be visualized while the spectra are acquired. Modifications concerning pure variable selection and determination of the number of component have been made to the SIMPLISMA algorithm for real-time processing. The VI determined the component number automatically. The time constraints of the real-time algorithm were compared to SIMPLISMA and standard data acquisition.

Real-time processing algorithms for target detection and classification in hyperspectral imagery

The authors present a linearly constrained minimum variance (TCMV) beamforming approach to real time processing algorithms for target detection and classification in hyperspectral imagery. The only required knowledge for these LCMV-based algorithms is targets of interest. The idea is to design a finite impulse response (FIR) filter to pass through these targets using a set of linear constraints while also minimizing the variance resulting from unknown signal sources. Two particular LCMV-based target detectors, the constrained energy minimization (CEM) and the target-constrained interference-minimization filter (TCIMF), are presented. In order to expand the ability of the LCMV-based target detectors to classification, the LCMV approach is further generalized so that the targets can be detected and classified simultaneously. By taking advantage of the LCMV-based filter structure, the LCMV-based target detectors and classifiers can be implemented by a QR-decomposition and be processed line-by-line in real time. The experiments using HYDICE and AVIRIS data are conducted to demonstrate their real time implementation.

Control of a Robot Based on Fusion of Visual and Force/Torque Sensor Information. Manipulation of a Deformable Object.

Since there exist a lot of deformable objects in our daily life, method of manipulation of a deformable object for a robot is expected not only in industrial manufacturing but also in life support. Generally, a force/torque sensor is used in playing a contact task for a rigid object by a robot. However, only a force/torque sensor is not enough in handling of a deformable object by a robot. In this paper, a fusion algorithm by integrating data from both a force/torque sensor and a visual sensor is proposed for a robot to play a contact task in which an aluminum peg fixed on the robot hand is inserted into a hole installed on a deformable plate. To complete the task, a high-speed camera is used and a real time processing algorithm is developed to detect deformation of the central line of the hole. Then, the results of visual processing are integrated with data of the force/torque sensor using the proposed compliance control algorithm for a robot in playing the task. The effectiveness of the proposed method has been demonstrated through experiments.

The Neurally Controlled Animat: Biological Brains Acting with Simulated Bodies.

The brain is perhaps the most advanced and robust computation system known. We are creating a method to study how information is processed and encoded in living cultured neuronal networks by interfacing them to a computer-generated animal, the Neurally-Controlled Animat, within a virtual world. Cortical neurons from rats are dissociated and cultured on a surface containing a grid of electrodes (multi-electrode arrays, or MEAs) capable of both recording and stimulating neural activity. Distributed patterns of neural activity are used to control the behavior of the Animat in a simulated environment. The computer acts as its sensory system providing electrical feedback to the network about the Animat's movement within its environment. Changes in the Animat's behavior due to interaction with its surroundings are studied in concert with the biological processes (e.g., neural plasticity) that produced those changes, to understand how information is processed and encoded within a living neural network. Thus, we have created a hybrid real-time processing engine and control system that consists of living, electronic, and simulated components. Eventually this approach may be applied to controlling robotic devices, or lead to better real-time silicon-based information processing and control algorithms that are fault tolerant and can repair themselves.