The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform

Kou-yuan Huang - One of the best experts on this subject based on the ideXlab platform.

  • Seismic Signal Classification Using Perceptron with Different Learning Rules
    IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
    Co-Authors: Kou-yuan Huang, Fajar Abdurrahman
    Abstract:

    In a seismogram, there exist many kinds of wavelets. It can be classified into two classes. One class is normal, the other is abnormal. The abnormal may be the bright Spot Pattern caused from the gas sand zone. It has the properties of high amplitude and low frequency content in the wavelets. Perceptron is adopted to classify YXB9-02542-B100these two classes. Four different learning rules are used in the training of perceptron. Those are the fixed-increment, normalized perceptron, fractional correction, and absolute correction rules. The experiments are in the simulated and real seismograms. For the comparison of four learning rules in the experiment of simulated seismogram, the absolute correction rule can get the fastest convergence. Then, it is applied to the real seismic data. The bright Spot Pattern can be detected. The result can improve the seismic interpretation.

  • Seismic Pattern recognition using cellular neural network
    2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
    Co-Authors: Kou-yuan Huang, Wen-hsuan Hsieh
    Abstract:

    Cellular neural network is adopted for seismic Pattern recognition. We design cellular neural network to behave as associative memory according to the stored Patterns, and finish the training process of the network. Then we use this associative memory to recognize seismic test Patterns. In the experiments, the analyzed seismic Patterns are bright Spot Pattern, right and left pinch-out Patterns. From the recognition results, the noisy seismic Patterns can be recovered. Seismic Pattern recognition can help the analysis and interpretation of seismic data.

  • Cellular neural network for seismic horizon picking
    2005 9th International Workshop on Cellular Neural Networks and Their Applications, 2005
    Co-Authors: Kou-yuan Huang, Chin-hua Chang, Wen-shiang Hsieh, Shan-chih Hsieh, L.k. Wang, Fan-jen Tsai
    Abstract:

    Cellular neural network has the property of local connection. We use this property for seismic horizon linking. The constraint conditions for detecting seismic horizons are used to construct the Lyapunov energy function. The connection weights between neurons are extracted from Lyapunov energy function. Substitute the connection weights into the equation of motion, the next state value of each neuron can be calculated. After training, we apply the equation of motion to seismic horizon linking. From the experimental results in seismic bright Spot Pattern, the picked horizons can match the visual inspection. The automatic seismic horizon picking can help the seismic data processing and improve the seismic interpretation.

  • Neural network for seismic principal components analysis
    IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999
    Co-Authors: Kou-yuan Huang
    Abstract:

    The neural network using an unsupervised generalized Hebbian algorithm (GHA) is adopted to find the principal eigenvectors of a covariance matrix in different kinds of seismograms. We have shown that the extensive computer results of the principal components analysis (PCA) using neural net of GHA can extract the information of seismic reflection layers and uniform neighboring traces. The analyzed seismic data are the seismic traces with 20, 25, and 30 Hz Ricker wavelets, the fault, the reflection and diffraction Patterns after NMO correction, the bright Spot Pattern, and the real seismogram at Mississippi Canyon. The properties of high amplitude, low frequency, and polarity reversal can be shown from the projections on the principal eigenvectors. For PCA, a theorem is proposed that adding extra point along the direction of the existing eigenvector can enhance that eigenvector. The theorem is applied to the interpretation of a fault seismogram and the uniform property of other seismograms. The PCA also provides a significant seismic data compression.

  • Neural computing for seismic principal components analysis
    IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Developme, 1997
    Co-Authors: Kou-yuan Huang
    Abstract:

    The neural network of the unsupervised generalized Hebbian algorithm (GHA) is adopted to find the principal eigenvectors of a covariance matrix in different kinds of seismograms. The theorem about the effect of adding one extra point along the direction of the eigenvector is proposed to help the interpretations that more uniform data vectors along one principal eigenvector direction can enhance the eigenvalue. Diffraction Pattern, fault Pattern, bright Spot Pattern and real seismograms are in the experiments. From analyses the principal components can show the high amplitude, polarity reversal, and low frequency wavelet in the detection of seismic anomalies and can improve seismic interpretations.

Robert L Lesser - One of the best experts on this subject based on the ideXlab platform.

  • leopard Spot Pattern of yellowish subretinal deposits in central serous chorioretinopathy
    Archives of Ophthalmology, 2002
    Co-Authors: Tomohiro Iida, Richard F Spaide, Anton Haas, Lawrence A Yannuzzi, Lee M Jampol, Robert L Lesser
    Abstract:

    Objective To describe clinical and angiographic features of patients with central serous chorioretinopathy (CSC) who had yellowish subretinal deposits forming a reticulated leopard-Spot Pattern during fluorescein angiography. Methods We conducted case studies using the clinical and photographic records of 5 patients. Results All 5 patients were older men between the ages of 68 and 81 years who had been treated with corticosteroids and had bilateral CSC. Nine eyes of the 5 patients developed yellowish deposits in a reticulated Pattern in the macular region under the chronic detached neurosensory retina. The Pattern of leopard-Spot deposits was well demonstrated on the fluorescein angiogram, with hypofluorescence in most of the deposits and hyperfluorescence from atrophy of the retinal pigment epithelium. Later phases of the fluorescein angiographic study showed leaks from the retinal pigment epithelium. During the indocyanine green angiography evaluation of 4 patients, all had bilateral multifocal patches of hyperfluorescence in the midphase, findings typical of CSC. Conclusions Yellowish deposits forming a reticulated leopard-Spot Pattern may occur under the neurosensory retina and are associated with chronic neurosensory detachment caused by CSC. All patients were older men being treated with corticosteroids. This report described a newly recognized finding: the subretinal deposition of a yellowish material in a leopard-Spot Pattern in eyes with CSC.

Frank K Tittel - One of the best experts on this subject based on the ideXlab platform.

  • Generalized optical design of two-spherical-mirror multi-pass cells with dense multi-circle Spot Patterns
    Applied Physics Letters, 2020
    Co-Authors: Lei Dong, Hongpeng Wu, Weidong Chen, Frank K Tittel
    Abstract:

    We report a set of practical multi-circle Spot Patterns produced by two-spherical-mirror multi-pass cells (MPCs). Such a set of intricate Spot Patterns takes full account of the evolution and deformation of Spot shapes caused by aberrations on two spherical mirror surfaces by means of a multi-ray calculation model, thus avoiding Spot overlaps and reducing an etalon effect. An eight- and nine-multi-circle Spot Pattern was demonstrated experimentally in order to verify the validity of the calculated results. Furthermore, a 2f spectrum measurement of ambient methane was performed using the eight-multi-circle Spot Pattern MPC to verify the practicability. An approach to search for multi-circle Spot Patterns in a two-spherical-mirror MPC is discussed in detail. A set of dense Spot Patterns results in sensitive, low-cost, compact trace gas sensors based on MPCs, which can be used to implement a large-scale deployment of distributed sensor networks for monitoring pollutants or to realize handheld mobile sensor devices for safety inspection, leakage detection, and medical diagnostics.

  • calculation model of dense Spot Pattern multi pass cells based on a spherical mirror aberration
    Optics Letters, 2019
    Co-Authors: Lei Dong, Hongpeng Wu, Shangzhi Li, Lei Zhang, Frank K Tittel
    Abstract:

    We report a novel calculation model for dense Spot Pattern multi-pass cells consisting of two common identical spherical mirrors. A modified ABCD matrix without the paraxial approximation was developed to describe the ray propagation between two spherical mirrors and the reflection on the mirror surfaces. The intrinsic aberration from the spherical curvature creates a set of intricate variants with respect to a standard Herriot circle Spot Pattern. A series of detailed numerical simulations are implemented to verify that the input and output beams remain the same and, hence, retrace the same ray Pattern. The set of exotic Spot Patterns obtained with a high fill factor improves the utilization efficiency of the mirror surfaces and produces a longer total optical path length with a low mirror cost.

Miles J. Padgett - One of the best experts on this subject based on the ideXlab platform.

  • An SLM-based Shack-Hartmann wavefront sensor for aberration correction in optical tweezers
    Journal of Optics, 2010
    Co-Authors: Richard W. Bowman, Amanda J. Wright, Miles J. Padgett
    Abstract:

    Holographic optical tweezers allow the creation of multiple optical traps in 3D configurations through the use of dynamic diffractive optical elements called spatial light modulators (SLMs). We show that, in addition to controlling traps, the SLM in a holographic tweezers system can be both the principal element of a wavefront sensor and the corrective element in a closed-loop adaptive optics system. This means that aberrations in such systems can be estimated and corrected without altering the experimental setup. Aberrations are estimated using the Shack?Hartmann method, where an array of Spots is projected into the sample plane and the distortion of this array is used to recover the aberration. The system can recover aberrations of up to ten wavelengths peak?peak, and is sensitive to aberrations much smaller than a wavelength. The Spot Pattern could also be analysed by eye, as a tool for aligning the system.

Tomohiro Iida - One of the best experts on this subject based on the ideXlab platform.

  • leopard Spot Pattern of yellowish subretinal deposits in central serous chorioretinopathy
    Archives of Ophthalmology, 2002
    Co-Authors: Tomohiro Iida, Richard F Spaide, Anton Haas, Lawrence A Yannuzzi, Lee M Jampol, Robert L Lesser
    Abstract:

    Objective To describe clinical and angiographic features of patients with central serous chorioretinopathy (CSC) who had yellowish subretinal deposits forming a reticulated leopard-Spot Pattern during fluorescein angiography. Methods We conducted case studies using the clinical and photographic records of 5 patients. Results All 5 patients were older men between the ages of 68 and 81 years who had been treated with corticosteroids and had bilateral CSC. Nine eyes of the 5 patients developed yellowish deposits in a reticulated Pattern in the macular region under the chronic detached neurosensory retina. The Pattern of leopard-Spot deposits was well demonstrated on the fluorescein angiogram, with hypofluorescence in most of the deposits and hyperfluorescence from atrophy of the retinal pigment epithelium. Later phases of the fluorescein angiographic study showed leaks from the retinal pigment epithelium. During the indocyanine green angiography evaluation of 4 patients, all had bilateral multifocal patches of hyperfluorescence in the midphase, findings typical of CSC. Conclusions Yellowish deposits forming a reticulated leopard-Spot Pattern may occur under the neurosensory retina and are associated with chronic neurosensory detachment caused by CSC. All patients were older men being treated with corticosteroids. This report described a newly recognized finding: the subretinal deposition of a yellowish material in a leopard-Spot Pattern in eyes with CSC.