The Reinvention of Holography

2014 ◽  
pp. 167-211
Author(s):  
Frank C. Fan ◽  
C. C. Jiang ◽  
Sam Choi
Keyword(s):  
Real Time ◽  
Digital Holography ◽  
Fourier Transforms ◽  
Spatial Spectrum ◽  
Quantum Model ◽  
Image Information ◽  
Underlying Theory ◽  
Spatial Spectra

In this chapter, the authors examine the concept of 3-D displays with sampled spatial spectra in discrete hoxels, reducing the redundancy present in digital holography, which prints each individual hogel. The underlying theory deals with the principles of 3-D imaging using the quantum model and 4-D (x,y,z,t) Fourier transforms. The image information is treated as a single spatial spectrum and its 3-D information recovered by digital vector treatment through hoxels. This enable the achievement of real-time communication in 3-D.

scholarly journals High-Bandpass Filters in Electrocardiography: Source of Error in the Interpretation of the ST Segment

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
F. Buendía-Fuentes ◽  
M. A. Arnau-Vives ◽  
A. Arnau-Vives ◽  
Y. Jiménez-Jiménez ◽  
J. Rueda-Soriano ◽  
...  
Keyword(s):  
Real Time ◽  
Fourier Transforms ◽  
Pass Filter ◽  
Discrete Fourier Transforms ◽  
Real Time Mode ◽  
Asymptomatic Patients ◽  
St Segment ◽  
Coronary Syndromes ◽  
Clinically Significant ◽  
High Pass

Introduction. Artifactual variations in the ST segment may lead to confusion with acute coronary syndromes. Objective. To evaluate how the technical characteristics of the recording mode may distort the ST segment. Material and Method. We made a series of electrocardiograms using different filter configurations in 45 asymptomatic patients. A spectral analysis of the electrocardiograms was made by discrete Fourier transforms, and an accurate recomposition of the ECG signal was obtained from the addition of successive harmonics. Digital high-pass filters of 0.05 and 0.5 Hz were used, and the resulting shapes were compared with the originals. Results. In 42 patients (93%) clinically significant alterations in ST segment level were detected. These changes were only seen in “real time mode” with high-pass filter of 0.5 Hz. Conclusions. Interpretation of the ST segment in “real time mode” should only be carried out using high-pass filters of 0.05 Hz.

scholarly journals Monitoring and Analysis of Wave Characteristics during Pipeline End Termination Installation

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 569
Author(s):  
Duanfeng Han ◽  
Ting Cui ◽  
Lihao Yuan ◽  
Yingfei Zan ◽  
Zhaohui Wu
Keyword(s):  
Real Time ◽  
Wave Motion ◽  
Fourier Transforms ◽  
Classical Method ◽  
Suitable Model ◽  
Wave Data ◽  
Wave Characteristics ◽  
Environmental Monitoring System ◽  
Spreading Function ◽  
Marine Environmental

Pipeline end termination (PLET) installation is an essential part of offshore pipe-laying operation. Pipe-laying operations are sensitive to pipe-laying barge motion and marine environmental conditions. Monitoring the field environment can provide a reasonable basis for planning pipe-laying. Therefore, the measurement and analysis of sea wave motion is helpful for the control and operational safety of the pipeline and vessels. In this study, an environmental monitoring system was established to measure wave motion during PLET operation. Fourier transforms were used to process images that were acquired by ultra-high-frequency X-band marine radar to extract wave parameters. The resulting wave spectra, as measured each minute, were used to simulate real-time wave data and calculate wave characteristics and regressed wave frequency and direction spectrum throughout the PLET operation. The regressed frequency, spectral density, and direction spectra were compared with the theoretical spectra to evaluate their similarity and find the most similar spreading function in the operational area (the South China Sea). Gaussian fitting of real-time wave data was tested while using a classical method. The marginal distribution and joint density of the wave characteristics were estimated and then compared with theoretical distributions to find the most suitable model for improving marine environmental forecasting.

A hybrid fuzzy quantum time series and linear programming model: Special application on TAIEX index dataset

2019 ◽  
Vol 34 (25) ◽  
pp. 1950201 ◽  
Author(s):  
Pritpal Singh ◽  
Gaurav Dhiman ◽  
Sen Guo ◽  
Ritika Maini ◽  
Harsimran Kaur ◽  
...  
Keyword(s):  
Time Series ◽  
Linear Programming ◽  
Real Time ◽  
Time Series Data ◽  
Programming Model ◽  
Series Data ◽  
Quantum Model ◽  
Quantum Time ◽  
Degree Of Membership ◽  
Quantum Approach

The supremacy of quantum approach is able to provide the solutions which are not practically feasible on classical machines. This paper introduces a novel quantum model for time series data which depends on the appropriate length of intervals. In this study, the effects of these drawbacks are elaborately illustrated, and some significant measures to remove them are suggested, such as use of degree of membership along with mid-value of the interval. All these improvements signify the effective results in case of quantum time series, which are verified and validated with real-time datasets.

Direct quantitative imaging of the writing stage in a photosensitive azopolymer by digital holography

Soft Matter ◽  
2019 ◽  
Vol 15 (39) ◽  
pp. 7809-7813 ◽  
Author(s):  
V. Pagliarulo ◽  
A. Calabuig ◽  
S. Grilli ◽  
P. Ferraro
Keyword(s):  
Thin Films ◽  
Real Time ◽  
Surface Relief ◽  
Digital Holography ◽  
Light Exposure ◽  
Quantitative Imaging ◽  
Continuous Light ◽  
Full Field ◽  
Surface Relief Grating

In this paper, we demonstrated that the gradual formation of a surface relief grating (SRG) in azopolymer thin films under continuous light exposure could be directly observed in situ and in real-time, allowing full-field characterization.

scholarly journals SurfNetv2: An Improved Real-Time SurfNet and Its Applications to Defect Recognition of Calcium Silicate Boards

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4356 ◽  
Author(s):  
Chi-Yi Tsai ◽  
Hao-Wei Chen
Keyword(s):  
Real Time ◽  
Calcium Silicate ◽  
Surface Defect ◽  
Surface Defects ◽  
Visual Image ◽  
Training Dataset ◽  
Image Information ◽  
Training Stage ◽  
High Recognition Accuracy ◽  
Defect Recognition

This paper presents an improved Convolutional Neural Network (CNN) architecture to recognize surface defects of the Calcium Silicate Board (CSB) using visual image information based on a deep learning approach. The proposed CNN architecture is inspired by the existing SurfNet architecture and is named SurfNetv2, which comprises a feature extraction module and a surface defect recognition module. The output of the system is the recognized defect category on the surface of the CSB. In the collection of the training dataset, we manually captured the defect images presented on the surface of the CSB samples. Then, we divided these defect images into four categories, which are crash, dirty, uneven, and normal. In the training stage, the proposed SurfNetv2 is trained through an end-to-end supervised learning method, so that the CNN model learns how to recognize surface defects of the CSB only through the RGB image information. Experimental results show that the proposed SurfNetv2 outperforms five state-of-the-art methods and achieves a high recognition accuracy of 99.90% and 99.75% in our private CSB dataset and the public Northeastern University (NEU) dataset, respectively. Moreover, the proposed SurfNetv2 model achieves a real-time computing speed of about 199.38 fps when processing images with a resolution of 128 × 128 pixels. Therefore, the proposed CNN model has great potential for real-time automatic surface defect recognition applications.

Real-time phase reconstruction of dual-wavelength off-axis digital holography based on Java and GPU

2020 ◽  
Author(s):  
Yunze Cao ◽  
Wanchen Li ◽  
Mingguang Shan ◽  
Zhi Zhong ◽  
Lei Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Digital Holography ◽  
Dual Wavelength ◽  
Phase Reconstruction

scholarly journals Underwater Ambiguity Elimination Method Based on Co-Prime Sensor Array

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6058
Author(s):  
Tian Lan ◽  
Yilin Wang ◽  
Longhao Qiu
Keyword(s):  
High Resolution ◽  
Sensor Array ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Spatial Spectrum ◽  
Estimation Methods ◽  
Sensing Applications ◽  
Passive Sensing ◽  
Spatial Spectra ◽  
Beam Patterns

Recently, the direction of arrival estimation with co-prime arrays has gradually been applied in underwater scenarios because of its significant advantages over traditional uniform linear arrays. Despite the advantages of co-prime arrays, the spatial spectra obtained directly from conventional beamforming can be degraded by grating lobes due to the sparse spatial sampling in passive sensing applications, which will seriously deteriorate the estimation performance. In this paper, capon beamforming is applied to a co-prime sensor array as a pretreatment before high-resolution direction of arrival (DOA) estimation methods. The amplitudes extracted from the beam-domain outputs of two subarrays and the phases extracted from the cross-spectrum of the spatial spectrum are exploited to suppress the spurious peaks in beam patterns and eliminate ambiguities. Consequently, interference can be further mitigated, and the performance of high-resolution DOA methods will be guaranteed. Simulations show that the method proposed can improve the reliability and accuracy of DOA estimation with great value in practice.

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