Real-Time Discrete Adaptive Control of Robot Arm Based on Digital Signal Processing

A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.

100 Gb/s coherent chaotic optical communication over 800 km fiber transmission via advanced digital signal processing

Chaotic optical communication has shown large potential as a hardware encryption method in the physical layer.As an important figure of merit,the bit rate–distance product of chaotic optical communication has been continually improved to 30 Gb/s×340 km,but it is still far from the requirement for a deployed optical fiber communication system,which is beyond 100 Gb/s×1000 km.A chaotic carrier can be considered as an analog signal and suffers from fiber channel impairments,limiting the transmission distance of high-speed chaotic optical communications.To break the limit,we propose and experimentally demonstrate a pilot-based digital signal processing scheme for coherent chaotic optical communication combined with deep-learning-based chaotic synchronization.Both transmission impairment recovery and chaotic synchronization are realized in the digital domain.The frequency offset of the lasers is accurately estimated and compensated by determining the location of the pilot tone in the frequency domain,and the equalization and phase noise compensation are jointly performed by the least mean square algorithm through the time domain pilot symbols.Using the proposed method,100 Gb∕s chaotically encrypted quadrature phase-shift keying(QPSK)signal over 800 km single-mode fiber(SMF)transmission is experimentally demonstrated.In order to enhance security,40 Gb∕s real-time chaotically encrypted QPSK signal over 800 km SMF transmission is realized by inserting pilot symbols and tone in a field-programmable gate array.This method provides a feasible approach to promote the practical application of chaotic optical communications and guarantees the high security of chaotic encryption.

High Resolution Radar Real-Time Signal and Information Processing

Radar is an electronic device that uses radio waves to determine the range, angle, or velocity of objects. Real-time signal and information processor is an important module for real-time positioning, imaging, detection and recognition of targets. With the development of ultra-wideband technology, synthetic aperture technology, signal and information processing technology, the radar coverage, detection accuracy and resolution have been greatly improved, especially in terms of one-dimensional(1D) high-resolution radar detection, tracking, recognition, and two-dimensional(2D) synthetic aperture radar imaging technology. Meanwhile, for the application of radar detection and remote sensing with high resolution and wide swath, the amount of data has been greatly increased. Therefore, the radar is required to have low-latency and real-time processing capability under the constraints of size, weight and power consumption. This paper systematically introduces the new technology of high resolution radar and real-time signal and information processing. The key problems and solutions are discussed, including the detection and tracking of 1D high-resolution radar, the accurate signal modeling and wide-swath imaging for geosynchronous orbit synthetic aperture radar, and real-time signal and information processing architecture and efficient algorithms. Finally, the latest research progress and representative results are presented, and the development trends are prospected.

Digital Signal Processing Based Real Time Vehicular Detection System

Traffic monitoring is of major importance for enforcing traffic management policies.To accomplish this task,the detection of vehicle can be achieved by exploiting image analysis techniques.In this paper,a solution is presented to obtain various traffic parameters through vehicular video detection system(VVDS).VVDS exploits the algorithm based on virtual loops to detect moving vehicle in real time.This algorithm uses the background differencing method,and vehicles can be detected through luminance difference of pixels between background image and current image.Furthermore a novel technology named as spatio-temporal image sequences analysis is applied to background differencing to improve detection accuracy.Then a hardware implementation of a digital signal processing (DSP) based board is described in detail and the board can simultaneously process four-channel video from different cameras. The benefit of usage of DSP is that images of a roadway can be processed at frame rate due to DSP′s high performance.In the end,VVDS is tested on real-world scenes and experiment results show that the system is both fast and robust to the surveillance of transportation.

Kravchenko atomic transforms in digital signal processing

The modified atomic transformations are constructed and proved. On their basis the new complex analytic wavelets are obtained. The proof of the Fourier transforms existence in L~ and L2 on the basis of the theory of atomic functions （AF） are presented. The numerical experiments of digital time series processing and physical analysis of the results confirm the efficiency of the proposed transforms.

An acquisition system of digital nuclear signal processing for the algorithm development

A principle and method of constructing the digital acquisition system is presented in this work,which is convenient for the study on the theories and algorithms of digital nuclear signal processing.The hardware system of the digital acquisition system consists of front-end controller,waveform digitizer and PC workstation,on which the software system has been developed based on Visual C++under Windows environment.The alterable-frequency sampling(AFS)algorithm and the alterable-frequency trapezoidal filter(AFTF)algorithm have also been studied in the real-time environment,along with a digital nuclear spectrum acquisition system being set up based on the new algorithms and theγ-ray spectra of 241Am being shown.A useful experimental platform could be provided by this work for the successive work such as the development of global digitized nuclear measurement system and the study of digital nuclear signal processing.

New WA-system of kravchenko functions in digital signal processing

On the basis of modified atomic transformations the new WA-systems of Kravchenko functions are constructed.As an example the digital processing of time series of the various physical nature processing is considered.The numerical experiments and physical analysis of the results confirm the efficiency of the proposed WA-systems of Kravchenko functions.

A beam position measurement system of fully digital signal processing at SSRF

This fully digital beam position measurement instrument is designed for beam position monitoring and machine research in Shanghai Synchrotron Radiation Facility. The signals received from four position-sensitive detectors are narrow pulses with a repetition rate up to 499.654 MHz and a pulse width of around 100 ps, and their dynamic range could vary over more than 40 dB in machine research. By the employment of the under-sampling technique based on high-speed high-resolution A/D conversion, all the processing procedure is performed fully by the digital signal processing algorithms integrated in one single Field Programmable Gate Array. This system functions well in the laboratory and commissioning tests, demonstrating a position resolution (at the turn by turn rate of 694 kHz) better than 7 μm over the input amplitude range of -40 dBm to 10 dBm which is well beyond the requirement.

DIGITAL PROCESSING OF THE POLARIZATION STATE OF GEOPHYSICAL ULF SIGNALS

In this paper, the evaluation by running window smoothing is used for the digital processing of the polarization of geophysical ULF signals. The observed signals are resolved into two orthogonal complex components so that it is no longer necessary to consider the phase and amplitude of the signals simultaneously.

Description and reconstruction of one-dimensional photonic crystal by digital signal processing theory

A method of describing one-dimensional photonic crystals （1DPCs） based on Z-domain digital signal processing theory is presented. The analytical expression of the target band gap spectrum in the digital domain is obtained by the autocorrelation of its impulse response. The feasibility of this method is verified by reconstructing two simple 1DPC structures with a target photonic band gap obtained by the traditional transfer matrix method. This method provides an effective approach to function-guided designs of interference-based band gap structures for photonic applications.

Digital Signal Processing for Optical Access Networks

In this paper, we investigate advanced digital signal process ing （DSP） at the transmitter and receiver side for signal pre equalization and postequalization in order to improve spec trum efficiency （SE） and transmission distance in an optical access network. A novel DSP scheme for this optical super Nyquist filtering 9 Quadrature Amplitude Modulation （9 QAM） like signals based on muhimodulus equalization with out post filtering is proposed. This scheme recovers the Ny quist filtered Quadrature PhaseShift Keying （QPSK） signal to a 9QAMlike one. With this technique, SE can be increased to 4 b/s/Hz for QPSK signals. A novel digital superNyquist signal generation scheme is also proposed to further suppress the Nyquist signal bandwidth and reduce channel crosstalk without the need for optical prefiltering. Only optical cou plers are needed for superNyquist wavelengthdivisionmulti plexing （WDM） channel multiplexing. We extend the DSP for shorthaul optical transmission networks by using highorder QAMs. We propose a highspeed Can＇ierless Amplitude/Phase 64 QAM （CAP64 QAM） system using directly modulated la ser （DML） based on direct detection and digital equalization. Decisiondirected least mean square is used to equalize the CAP64QAM. Using this scheme, we generate and transmit up to 60 Gbit/s CAP64QAM over 20 km standard single mode fiber based on the DML and direct detection. Finally, several key problems are solved for real time orthogonalfre quencydivisionmultiplexing （OFDM） signal transmission aml processing. With coherent detection, up to 100 Glfit/s 16 QAMOFDM realtime transmission is possible.

Low-Power Operational Amplifier for Real-Time Signal Processing System of Micro Air Vehicle

A low-power complementary metal oxide semiconductor（CMOS） operational amplifier （op-amp） for real-time signal processing of micro air vehicle （MAV） is designed in this paper.Traditional folded cascode architecture with positive channel metal oxide semiconductor（PMOS） differential input transistors and sub-threshold technology are applied under the low supply voltage.Simulation results show that this amplifier has significantly low power,while maintaining almost the same gain,bandwidth and other key performances.The power required is only 0.12 mW,which is applicable to low-power and low-voltage real-time signal acquisition and processing system.

Interface Design Of Digital Platform For Bio Signal Processing

Bio-sensor arrays for multi-channel recording have been developed recently and signal processing platforms for those signals have been studied actively.But it’s thereal situation which these technologies are generally developed and studied respectively.So the interface design between recording array and signal processing platform is also an important issue to make bio-sensor signal processing system.In this paper,we proposed interface which has unique protocols to control sensor array and operate platform.There are two types of protocols in the interface.One is between sensor array and MCU in platform and the other is between MCU and board for wireless communication.Basically,each protocol has two kinds of modes(single,frame)and it can be extended if needed.

Design and Construction of a Digital Multichannel Analyzer for HPGe Detector Using Digital Signal Processing Technique

The outstanding advantage of digital signal processing (DSP) techniques and Field Programmable Gate Array (FPGA) technology is capable of improving the quality of the experimental measurements for nuclear radiation. In this article, a compact DMCA 8 K was designed and manufactured using DSP technique based on FPGA technology. In particular, the output of the preamplifier is completely processed by digital techniques which are obtained from the analog-to-digital converter (ADC) to calculate the baseline, DC offset, energy peaks, pile up, threshold discrimination and then the form of energy spectrum. The Spartan-6 board is used as a hardware for the development of the digital multichannel analyzer (DMCA), which is equipped with the 14-bit AD6645 with 62.5 Msps sample rate. The application software for instrument control, data acquisition and data processing was written under C++ builder via the RS-232 interface. The designed DMCA system has been tested with a HPGe detector using gamma sources of 60Co and 137Cs and a reference pulser.

Adaptive and Intelligent Digital Signal Processing for Improved Optical Interconnection

In recent years, explosively increasing data traffic has been boosting the con?tinuous demand of high speed optical interconnection inside or among data centers, high performance computers and even consumer electronics. To pursue the improved intercon?nection performance of capacity, energy efficiency and simplicity, effective approaches are demonstrated including particularly advanced digital signal processing (DSP) meth?ods. In this paper, we present a review about the enabling adaptive DSP methods for opti?cal interconnection applications, and a detailed summary of our recent and ongoing works in this field. In brief, our works focus on dealing with the specific issues for short-reach interconnection scenarios with adaptive operation, including signal-to-noise-ratio (SNR) limitation, level nonlinearity distortion, energy efficiency consideration and the de?cision precision.

Virtual Experimental Project Design in the Digital Signal Processing Course

This paper proposes the design and development of virtual experimental projects in the Digital Signal Processing course,using MATLAB,Proteus,and CCS platforms to develop a library of typical experimental cases for biomedical engineering majors and discusses the design process.Based on these typical cases,this paper explores the secondary design for innovative engineering practice case teaching,which can promote students’understanding and mastery of digital signal processing theories,algorithms,and technologies in an intuitive,flexible,and efficient way;quickly build new innovative engineering case models and further cultivate students’engineering application ability as well as innovative thinking.

Implementation of a cusp-like for real-time digital pulse shaper in nuclear spectrometry

Pulse shaping,which improves signal-to-noise ratio excellently,has been extensively used in nuclear signal processing.This paper presents a cusp-like pulse-shaping technique developed through the recursive difference equation in time domain.It can be implemented in field programmable gate array hardware system.Another flat-topped cusp-like shaper is developed to optimize the time constant of pulse shaping and reduce the influence of ballistic deficit.The methods of both baseline restoration and pile-up rejection are described.The ^(137)Cs energy spectra measured with the digital cusp-like shaper are 6.6% energy resolution,while those by traditional analog pulse shaper are 7.2% energy resolution,under the same conditions.This technique offers flexibility,too,in adjusting the pulse shaper parameters.

Applications of advanced signal processing and machine learning in the neonatal hypoxic-ischemic electroencephalography

Perinatal hypoxic-ischemic-encephalopathy significantly contributes to neonatal death and life-long disability such as cerebral palsy. Advances in signal processing and machine learning have provided the research community with an opportunity to develop automated real-time identification techniques to detect the signs of hypoxic-ischemic-encephalopathy in larger electroencephalography/amplitude-integrated electroencephalography data sets more easily. This review details the recent achievements, performed by a number of prominent research groups across the world, in the automatic identification and classification of hypoxic-ischemic epileptiform neonatal seizures using advanced signal processing and machine learning techniques. This review also addresses the clinical challenges that current automated techniques face in order to be fully utilized by clinicians, and highlights the importance of upgrading the current clinical bedside sampling frequencies to higher sampling rates in order to provide better hypoxic-ischemic biomarker detection frameworks. Additionally, the article highlights that current clinical automated epileptiform detection strategies for human neonates have been only concerned with seizure detection after the therapeutic latent phase of injury. Whereas recent animal studies have demonstrated that the latent phase of opportunity is critically important for early diagnosis of hypoxic-ischemic-encephalopathy electroencephalography biomarkers and although difficult, detection strategies could utilize biomarkers in the latent phase to also predict the onset of future seizures.

Measuring Absolute Delay of RNSS Signal Channel Using Digital Envelope Detection

The absolute delay caused by equipment of radio navigation satellite service (RNSS) signal channel must be calibrated in the application of positioning. The measurement accuracy of absolute delay will affect the positioning precision of RNSS user. An absolute delay measurement technique using digital envelope detection was developed for RNSS signal transmission channel. The RNSS transmission signal of navigation satellite and the one pulse per second (1PPS)generated by satellite time keeping system were sampled synchronously. With sampling data of 1PPS,the reference point of the absolute delay can be decided at first,and then sampling data of RNSS transmission signal were truncated. The truncated data were processed using digital envelop detection algorithm to search the phase converting points of RNSS signal. Finally,the absolute delay of RNSS signal transmitting channel was calculated. Uncertainty of measurement with proposed technique is lower than 0. 2 ns as the sampling frequency is 10 GHz.

Digital Optical Signal Amplifier Using an Er-doped Fiber Optical Bistable Device

The principle and charecteristics of verious digital optical signal amplifiers using Er doped fiber optical bistability devices have been discussed. Optical signal gain and its variation with the parameters of the devices with constant or pulse optical bias have been calculated, and the design principle of those devices has been given.