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SAR image formation algorithms have implicit or explicit dependence on the mathematical model of the image observation process. Inaccuracies in the image model will bring phase error, which may cause various quality degradations in the reconstructed images, especially in the millimeter-wave or terahertz-waves radar. In this paper, we propose a sparse Bayesian approach for joint SAR imaging and phase...
Compressive sensing (CS) has been successfully used in synthetic aperture radar (SAR) imaging and shows the great potential. However, the existing CS-based SAR models assume the exact mathematical model of the observation process. In practice, the inaccuracy in the observation model will cause various degradation in the reconstructed SAR images, especially in the frequencies of millimeter-wave or...
A terahertz (THz) radar system with the highest frequency up to 0.22THz is described in this paper. The system is built based on the microwave up-conversion technology and with a good performance in operating range. The radar cross section (RCS) measurement of different objects, namely, corner reflector, cylinder, rectangular plate and a scale car model, is performed based on the THz system. By the...
With a two-compartment model, we investigate how subthreshold sinusoidal electric fields (EFs) affect neuronal discharges of active neurons by adjusting the field intensity and the field frequency. It's found that apparent fluctuations on neuronal discharges only appear within several stimulus frequency windows. And when the field frequency is adjusted to be close to the multiple of the intrinsic...
Multi-FPGA system for the design of the spiking neural network is a great challenge for hardware acceleration. Multilayer feedforward neural networks (FNNs) are vitally important for the study of the coding problems in sensory organs. In this paper a multilayer FNN is implemented on a multi-FPGA-based system, which can guarantee both the high computational efficiency and the large network scale. The...
The study of brain functional connectivity has become an important aspect of neuroscience. With the development of different methods to detect functional connectivity, the neural mass model based on physiology provides a basis for validating methods. As a popular method of discovering functional connectivity, Granger causality is applied to many fields of neurophysiology, but the mapping between Granger...
At the single neuron level, neural information processing involves the transformation of input stimulation into an output spike train. Here a generalized linear model (GLM) is used to reconstruct the mapping from stimulation to firing trains of single neuron for Hudgkin-Huxley (H-H) model. Firstly, H-H model is stimulated by the white noise to generate the input-output data samples used to construct...
Based on the two-compartment neuron model, the influence of neuronal morphology on firing and phase response curves (PRC) of cells are investigated. And by means of PRC, the relationship between neuronal morphology and network synchronization stimulated by extracellular electric field is studied. Results showed that the excitability of neurons can present different types when the morphological parameter...
Currently, open-loop deep brain stimulation is an effective treatment for Parkinson's disease, the stimulus waveforms are static high-frequency pulse sequences. In this paper the input-output feedback linearization method is introduced in the closed-loop control of Parkinsonian state based on a computational model. Closed-loop control effects are compared with the classical open-loop control. Simulation...
Previous studies indicate that the effectiveness of deep brain stimulation (DBS) is dependent on the stimulus parameters and the purpose of this study is to examine the effects of DBS amplitude on the basal-ganglia-thalamo-cortical (BG-TC) network activity through a computational model. Our results indicate that the relation between DBS amplitudes and TC relay reliability is nonmonotonic, effective...
Recent studies have suggested that endogenous electric fields can not only be considered as an observation window of neural activities but also form a feedback on membranes of adjacent cells which implies it may play an important role in network dynamic behaviors. However, the role of endogenous field feedback in the detectability of external weak signal is still unknown. In this study, we introduced...
Multilayer feedforward networks are related to functional groups of neurons where information is transmitted from one group to the next. It is a generic framework to characterize the properties of spiking activities in propagation. In this paper, we designed a novelty structure of feedforward network on FPGA to propagate the synchronous spiking activities. The experiment results demonstrate that the...
The compressive sensing (CS) has been successfully used in inverse synthetic aperture radar (ISAR) imaging. Since the sparse reconstruction based on l1 norm is sensitive to the regularized factor and makes it inconvenient to be used in practice, the sparse Bayesian learning (SBL) is considered in this situation, which retains a preferable property of the l0 norm and has no user parameter. In this...
This paper means to explore the application of input-output feedback linearization method to control the model-based firing behavior. The Pinsky-Rinzel (PR) model is used to develop the feedback controller. The epileptiform behavior is modeled by the high frequency burst of 29 Hz and the normal desired behavior is modeled by the periodic firing of 6 Hz. The epilepsy treatment is formulated as a classic...
The Parkinson's disease (PD) state can be distinguished by relay reliability of thalamic cell (TC). Among numerous parameters of single-compartment conductance-based TC model, only two of them mainly modulate the relay reliability of TC. In order to explore the relationship between the two parameters and the firing relay, a parameter estimation method based on particle swarm optimization (PSO) algorithm...
In this paper we develop an efficient anti-noise imaging algorithm based on Bayesian Compressive Sensing (BCS) theory. Random sampling is applied in range and azimuth direction respectively, and sparse dictionary matrixes are designed independently in each direction according to imaging geometry model. At last, BCS theory is used to reconstruct SAR image. BCS theory takes the prior knowledge of targets...
In this work a multiple-views real array imaging method for terahertz radar is demonstrated and theoretically explained based on synthetic aperture technique. Taking full advantage of short wavelength of terahertz wave, the real transreceiver array can provide high-resolution in transverse dimensions, while a wideband signal provides the resolution in the range dimension. Based on the inverse synthetic...
In this paper, we use the iterative learning control (ILC) algorithm to study the synchronization control of two Ghostburster neurons which are stimulated by two different external stimulus currents. At first, the periodic dynamic and chaos dynamic of two Ghostburster neurons are analyzed, which are stimulated by two situations of external stimulus currents. Then we design a kind of ILC controller...
Considering the frequency dispersion of the complex dielectric permittivity for metals, the accurate radar cross section (RCS) of a copper sphere is given from microwave to the optical frequency. By investigate the effects on the RCS caused by the dispersion of metals, we show that polished copper sphere can be treated as perfectly electrical conductor (PEC) for the RCS prediction at terahertz frequencies.
Electric steering gear is the executive body of aircraft maneuvers and an important part of aircraft guidance system. Based on a simplified model of electric steering gear for study, the first study includes the function and structure principle, the main performance parameters and failure thresholds, storage conditions and failure analysis of the electric steering gear. Secondly, the sensitivity of...
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