The Experts below are selected from a list of 21450 Experts worldwide ranked by ideXlab platform

J. K. Singh - One of the best experts on this subject based on the ideXlab platform.

  • Runoff prediction dynamic model based on transfer function for a small watershed
    Indian Journal of Soil Conservation, 2012
    Co-Authors: Pravendra Kumar, J. K. Singh
    Abstract:

    In this study, a variable storage coefficient conceptual model based on unit-step and transfer functions approach for Karkara watershed of Tilaiya dam catchment in Upper Damodar Valley of Jharkhand State, India was developed for estimating direct runoff hydrographs on storm basis. The rainfall data in blocks of finite duration are represented by the unit-step function in this model. Outflow hydrograph is obtained by Taking Inverse Laplace transform of product of Laplace transforms of Instantaneous Unit Hydrograph (IUH) and the input (effective rainfall). The ordinates of direct runoff hydrograph are computed by lagging the ordinates of outflow hydrographs by the effective rainfall block duration. The parameters i.e. storage coefficient and geometric ratio were estimated using the methods suggested by Sabol and method of moments using rainfall and runoff data of the watershed. The performance of the model was tested by comparing the computed direct runoff hydrographs with the observed runoff hydrographs. The model was calibrated for nine storm events and validated for three storm events. Based on the performance evaluation criteria model was found to be working well for the study area.

  • Runoff Prediction: Use of Muskingum Model for a Small Watershed
    Journal of Agricultural Engineering, 2012
    Co-Authors: Pravendra Kumar, J. K. Singh
    Abstract:

    An effort was made to develop a mathematical model using unit-step and transfer functions approach for Karkara watershed of Tilaiya dam catchment in Upper Damodar Valley of Jharkhand State of India for estimating direct runoff hydrographs on storm basis. The model used rainfall data in blocks of finite duration represented by unit step function. The outflow hydrograph ordinates were obtained by Taking Inverse Laplace transform of product of Laplace transforms of the transfer function (Laplace transform of Instantaneous Unit Hydrograph) and the input (effective rainfall). The direct runoff hydrograph ordinates were computed by lagging outflow hydrograph ordinates. Model parameter was estimated by Sabol method using rainfall and runoff data of the study watershed. The model was calibrated for nine storm events, and validated for three events. Quantitative performance of the model was tested using some of the widely used statistical indices as integral squared error, relative squared error and coefficient of efficiency. The estimated direct runoff hydrographs using the model were in close agreement with the observed direct runoff hydrographs. The developed model can be satisfactorily applied for prediction of storm direct runoff hydrographs from small watersheds in the study region.

Pravendra Kumar - One of the best experts on this subject based on the ideXlab platform.

  • Runoff prediction dynamic model based on transfer function for a small watershed
    Indian Journal of Soil Conservation, 2012
    Co-Authors: Pravendra Kumar, J. K. Singh
    Abstract:

    In this study, a variable storage coefficient conceptual model based on unit-step and transfer functions approach for Karkara watershed of Tilaiya dam catchment in Upper Damodar Valley of Jharkhand State, India was developed for estimating direct runoff hydrographs on storm basis. The rainfall data in blocks of finite duration are represented by the unit-step function in this model. Outflow hydrograph is obtained by Taking Inverse Laplace transform of product of Laplace transforms of Instantaneous Unit Hydrograph (IUH) and the input (effective rainfall). The ordinates of direct runoff hydrograph are computed by lagging the ordinates of outflow hydrographs by the effective rainfall block duration. The parameters i.e. storage coefficient and geometric ratio were estimated using the methods suggested by Sabol and method of moments using rainfall and runoff data of the watershed. The performance of the model was tested by comparing the computed direct runoff hydrographs with the observed runoff hydrographs. The model was calibrated for nine storm events and validated for three storm events. Based on the performance evaluation criteria model was found to be working well for the study area.

  • Runoff Prediction: Use of Muskingum Model for a Small Watershed
    Journal of Agricultural Engineering, 2012
    Co-Authors: Pravendra Kumar, J. K. Singh
    Abstract:

    An effort was made to develop a mathematical model using unit-step and transfer functions approach for Karkara watershed of Tilaiya dam catchment in Upper Damodar Valley of Jharkhand State of India for estimating direct runoff hydrographs on storm basis. The model used rainfall data in blocks of finite duration represented by unit step function. The outflow hydrograph ordinates were obtained by Taking Inverse Laplace transform of product of Laplace transforms of the transfer function (Laplace transform of Instantaneous Unit Hydrograph) and the input (effective rainfall). The direct runoff hydrograph ordinates were computed by lagging outflow hydrograph ordinates. Model parameter was estimated by Sabol method using rainfall and runoff data of the study watershed. The model was calibrated for nine storm events, and validated for three events. Quantitative performance of the model was tested using some of the widely used statistical indices as integral squared error, relative squared error and coefficient of efficiency. The estimated direct runoff hydrographs using the model were in close agreement with the observed direct runoff hydrographs. The developed model can be satisfactorily applied for prediction of storm direct runoff hydrographs from small watersheds in the study region.

Wenxing Bao - One of the best experts on this subject based on the ideXlab platform.

  • A New Technology of Remote Sensing Image Fusion
    Indonesian Journal of Electrical Engineering and Computer Science, 2012
    Co-Authors: Wei Feng, Wenxing Bao
    Abstract:

    To resolve the problem of multi-spectral remote sensing image fusion ?in this paper, we put forward an algorithm based on the wavelet packet and pulse-coupled neural network (PCNN) of remote sensing image fusion .The algorithm will be carried out as follows. Firstly, the TM images will be converted into HIS space, and then the luminance component and the high-resolution image will be broken into multi-scale by wavelet packet. Secondly, according to the frequency domain characteristics of the wavelet packet decomposition, we respectively use a method of weighted average in the low-frequency domain and a method of PCNN in the high frequency domain to select reconstruction coefficient.We can get a fused luminance component by Taking Inverse wavelet packet transform to be reconstructed. Finally, we can obtain the fusion image by Taking Inverse HIS transform. The experimental results show that the algorithm can be better to retain the image edge and texture details. Keywords : image fusion; HSI; wavelet packet; pulse coupled neural networks DOI:  http://dx.doi.org/10.11591/telkomnika.v10i3.617

  • An Improved Technology of Remote Sensing Image Fusion Based Waveled Packet and Pulse Coupled Neural Net
    TELKOMNIKA Telecommunication Computing Electronics and Control, 2012
    Co-Authors: Wei Feng, Wenxing Bao
    Abstract:

    To resolve the problem of multi-spectral remote sensing image fusion ?in this paper, we put forward an algorithm based on the wavelet packet and pulse-coupled neural network (PCNN) of remote sensing image fusion .The algorithm will be carried out as follows. Firstly, the TM images will be converted into HIS space, and then the luminance component and the high-resolution image will be broken into multi-scale by wavelet packet. Secondly, according to the frequency domain characteristics of the wavelet packet decomposition, we respectively use a method of weighted average in the low-frequency domain and a method of PCNN in the high frequency domain to select reconstruction coefficient.We can get a fused luminance component by Taking Inverse wavelet packet transform to be reconstructed. Finally, we can obtain the fusion image by Taking Inverse HIS transform. The experimental results show that the algorithm can be better to retain the image edge and texture details. Keywords : image fusion; HSI; wavelet packet; pulse coupled neural networks DOI:  http://dx.doi.org/10.11591/telkomnika.v10i3.617 Full Text: PDF

Jason L. Speyer - One of the best experts on this subject based on the ideXlab platform.

  • Sensor and Actuator Fault Reconstruction
    Journal of Guidance Control and Dynamics, 2004
    Co-Authors: R.h. Chen, Jason L. Speyer
    Abstract:

    Many fault detection filters have been developed to detect and identify sensor and actuator faults by using analytical redundancy. An approach to further reconstruct sensor and actuator faults from the residual generated by the fault detection filter is proposed. The transfer matrix from the faults to the residual is derived in terms of the eigenvalues of the fault detection filter associated with the detection spaces of the faults and the invariant zeros of the faults. For each fault, all possible fault reconstruction processes are derived and parameterized by applying a projector to the transfer matrix and Taking Inverse. Then, the optimal fault reconstruction process is determined by minimizing the ratio of the H 2 norm of the projected transfer matrix from the disturbance over the H 2 norm of the projected transfer matrix from the fault. For the existence of the fault reconstruction process, the invariant zeros of the fault have to be in the left-half plane. Furthermore, for reconstructing a sensor fault, the system has to be detectable with respect to the other sensors.

  • Fault reconstruction from sensor and actuator failures
    Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001
    Co-Authors: R.h. Chen, Jason L. Speyer
    Abstract:

    Many fault detection filters have been developed to detect and identify sensor and actuator faults by using analytical redundancy. In this paper, an approach for reconstructing sensor and actuator faults from the residual generated by the fault detection filter is proposed. The transfer matrix from the faults to the residual is derived in terms of the eigenvalues of the fault detection filter and the invariant zeros of the faults. For each fault, the fault reconstruction process is derived by applying a projector to the transfer matrix and Taking Inverse. In order to have a well-conditioned fault reconstruction process, the invariant zeros of the faults have to be in the left-half plane. Furthermore, for reconstructing a sensor fault, the system has to be detectable with respect to the other sensors.

Jiang Ze-tao - One of the best experts on this subject based on the ideXlab platform.

  • Image fusion based on nonsubsampled Contourlet transform and evaluation
    Application Research of Computers, 2009
    Co-Authors: Jiang Ze-tao
    Abstract:

    This paper introduced the characteristics of nonsubsampled Contourlet transform(NSCT),as well as its advantages in image transformation.NSCT was built upon nonsubsampled pyramids and nonsubsampled directional filter banks and it was a flexible multiscale,directional multiresolution and shift-unvariant image transform.Proposed a novel image fusion algorithm based on NSCT.Firstly,decomposed each source image in highpass subbands and lowpass subbands by NSCT.Secondly,used different fusion rules in different subbands,where local gradient preferential image fusion rule was adopted in highpass subbands and local energy preferential image fusion rule was adopted in lowpass subbandds.Finally,reconstructed the fused image by Taking Inverse transform of NSCT.The experimental results show that the performance of the novel algorithm is better than the traditional fusion algorithms based on wavelet transformation,and especially,the novel fusion algorithm can effectively eliminate the spectrum warping and the artificial edges caused by wavelet transform.

  • The Non-subsampled Directional Filter Bank and Its Application in Remote Sensing Image Fusion
    Journal of Image and Graphics, 2009
    Co-Authors: Jiang Ze-tao
    Abstract:

    The constructure of nonsubsampled directional filter bank(NSDFB)which is a full shift invariant is introduced,and a novel image fusion scheme based on NSDFB combining atrous wavelet transform for multispectral image(MS)and panchromatic image(PAN)is proposed.The intensity component I of MS obtained by intensity,hue and saturation(IHS)transform and the PAN are decomposed using atrous wavelet,and the high pass-bands are decomposed in multi-directional high pass-bands respectively by NSDFB.Then the high pass-bands and low pass-bands are fused by different fusion rules,and the I' component is reconstructed by Taking Inverse NSDFB decompose and Inverse a-trous wavelet transform.Finally,the fusion image is obtained by Inverse IHS transform of I' and the H,S component of MS.The experimental results show that the performance of the novel algorithm is better than IHS,principal component analysis(PCA)and the traditional fusion algorithms based on wavelet transformation,and especially can effectively eliminate the spectral distortion caused by PCA and wavelet transform.

  • Multi-sensor image fusion algorithm based on multi-directional àtrous wavelet transform
    Computer Engineering and Applications, 2008
    Co-Authors: Jiang Ze-tao
    Abstract:

    The construction of NonSubsampled Directional Filter Bank(NSDFB) and atrous wavelet transform which is full shift invariant are introduced,and a novel multi-sensor image fusion scheme based on NSDFB combining atrous wavelet transform for multi sensor images is proposed.Firstly,each source image is decomposed in highpass subbands and lowpass subbands by atrous wavelet transform,and the highpass subbands are decomposed in multi-directional high pass-bands respectively by NSDFB.Then different fusion rules are used in different subbands,where local gradient preferential image fusion rule is adopted in highpass subbands and average image fusion rule is adopted in lowpass subbandds.Finally the fused image is reconstructed by Taking Inverse NSDFB transform and Inverse atrous wavelet transform.The experimental results show that the performance of the novel algorithm is better than the traditional fusion algorithms based on wavelet transformation,and especially,the novel fusion algorithm can effectively eliminate the spectrum warping and the artificial edges caused by wavelet transform.