Relevant bibliographies by topics / Minimum mean square error

Academic literature on the topic 'Minimum mean square error'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 September 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Minimum mean square error.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Minimum mean square error"

1

Petra, Nicola, Davide De Caro, Valeria Garofalo, Ettore Napoli, and Antonio G. M. Strollo. "Truncated squarer with minimum mean-square error." Microelectronics Journal 45, no. 6 (June 2014): 799–804. http://dx.doi.org/10.1016/j.mejo.2014.02.018.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Piegorsch, Walter W., and A. John Bailer. "Minimum mean-square error quadrature." Journal of Statistical Computation and Simulation 46, no. 3-4 (May 1993): 217–34. http://dx.doi.org/10.1080/00949659308811504.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Schmidt, David A., Michael Joham, and Wolfgang Utschick. "Minimum mean square error vector precoding." European Transactions on Telecommunications 19, no. 3 (2008): 219–31. http://dx.doi.org/10.1002/ett.1192.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Chong, Edwin K. P. "Well-Conditioned Linear Minimum Mean Square Error Estimation." IEEE Control Systems Letters 6 (2022): 2431–36. http://dx.doi.org/10.1109/lcsys.2022.3162404.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Wen, Chao-Kai, Jung-Chieh Chen, and Pangan Ting. "A Shrinkage Linear Minimum Mean Square Error Estimator." IEEE Signal Processing Letters 20, no. 12 (December 2013): 1179–82. http://dx.doi.org/10.1109/lsp.2013.2283725.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Kullaa, Jyrki. "Sensor validation using minimum mean square error estimation." Mechanical Systems and Signal Processing 24, no. 5 (July 2010): 1444–57. http://dx.doi.org/10.1016/j.ymssp.2009.12.001.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Liski, Erkki P., Helge Toutenburg, and Götz Trenkler. "Minimum mean square error estimation in linear regression." Journal of Statistical Planning and Inference 37, no. 2 (November 1993): 203–14. http://dx.doi.org/10.1016/0378-3758(93)90089-o.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Purczyński, Jan. "Unbiased estimator versus minimum mean square error estimator." Studia i Prace WNEiZ 45 (2016): 61–70. http://dx.doi.org/10.18276/sip.2016.45/2-05.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Shah, M. C., R. Parmar, and V. P. Gupta. "Some techniques of minimum mean square error estimation." Microelectronics Reliability 28, no. 5 (January 1988): 689–91. http://dx.doi.org/10.1016/0026-2714(88)90004-2.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Weixian Qian, 钱惟贤, 陈钱 Qian Chen, and 顾国华 Guohua Gu. "Minimum mean square error method for stripe nonuniformity correction." Chinese Optics Letters 9, no. 5 (2011): 051003–51005. http://dx.doi.org/10.3788/col201109.051003.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Minimum mean square error"

1

Fodor, Balázs [Verfasser]. "Contributions to Statistical Modeling for Minimum Mean Square Error Estimation in Speech Enhancement / Balázs Fodor." Aachen : Shaker, 2015. http://d-nb.info/1070151815/34.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Xing, Chengwen, and 邢成文. "Linear minimum mean-square-error transceiver design for amplify-and-forward multiple antenna relaying systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44769738.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Nicolson, Aaron M. "Deep Learning for Minimum Mean-Square Error and Missing Data Approaches to Robust Speech Processing." Thesis, Griffith University, 2020. http://hdl.handle.net/10072/399974.

Full text
Abstract:
Speech corrupted by background noise (or noisy speech) can cause misinterpretation and fatigue during phone and conference calls, and for hearing aid users. Noisy speech can also severely impact the performance of speech processing systems such as automatic speech recognition (ASR), automatic speaker verification (ASV), and automatic speaker identification (ASI) systems. Currently, deep learning approaches are employed in an end-to-end fashion to improve robustness. The target speech (or clean speech) is used as the training target or large noisy speech datasets are used to facilitate multi-condition training. In this dissertation, we propose competitive alternatives to the preceding approaches by updating two classic robust speech processing techniques using deep learning. The two techniques include minimum mean-square error (MMSE) and missing data approaches. An MMSE estimator aims to improve the perceived quality and intelligibility of noisy speech. This is accomplished by suppressing any background noise without distorting the speech. Prior to the introduction of deep learning, MMSE estimators were the standard speech enhancement approach. MMSE estimators require the accurate estimation of the a priori signal-to-noise ratio (SNR) to attain a high level of speech enhancement performance. However, current methods produce a priori SNR estimates with a large tracking delay and a considerable amount of bias. Hence, we propose a deep learning approach to a priori SNR estimation that is significantly more accurate than previous estimators, called Deep Xi. Through objective and subjective testing across multiple conditions, such as real-world non-stationary and coloured noise sources at multiple SNR levels, we show that Deep Xi allows MMSE estimators to produce the highest quality enhanced speech amongst all clean speech magnitude spectrum estimators. Missing data approaches improve robustness by performing inference only on noisy speech features that reliably represent clean speech. In particular, the marginalisation method was able to significantly increase the robustness of Gaussian mixture model (GMM)-based speech classification systems (e.g. GMM-based ASR, ASV, or ASI systems) in the early 2000s. However, deep neural networks (DNNs) used in current speech classification systems are non-probabilistic, a requirement for marginalisation. Hence, multi-condition training or noisy speech pre-processing is used to increase the robustness of DNN-based speech classification systems. Recently, sum-product networks (SPNs) were proposed, which are deep probabilistic graphical models that can perform the probabilistic queries required for missing data approaches. While available toolkits for SPNs are in their infancy, we show through an ASI task that SPNs using missing data approaches could be a strong alternative for robust speech processing in the future. This dissertation demonstrates that MMSE estimators and missing data approaches are still relevant approaches to robust speech processing when assisted by deep learning.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Eng & Built Env
Science, Environment, Engineering and Technology
Full Text
APA, Harvard, Vancouver, ISO, and other styles
4

Nassr, Husam, and Kurt Kosbar. "PERFORMANCE EVALUATION FOR DECISION-FEEDBACK EQUALIZER WITH PARAMETER SELECTION ON UNDERWATER ACOUSTIC COMMUNICATION." International Foundation for Telemetering, 2017. http://hdl.handle.net/10150/626999.

Full text
Abstract:
This paper investigates the effect of parameter selection for the decision feedback equalization (DFE) on communication performance through a dispersive underwater acoustic wireless channel (UAWC). A DFE based on minimum mean-square error (MMSE-DFE) criterion has been employed in the implementation for evaluation purposes. The output from the MMSE-DFE is input to the decoder to estimate the transmitted bit sequence. The main goal of this experimental simulation is to determine the best selection, such that the reduction in the computational overload is achieved without altering the performance of the system, where the computational complexity can be reduced by selecting an equalizer with a proper length. The system performance is tested for BPSK, QPSK, 8PSK and 16QAM modulation and a simulation for the system is carried out for Proakis channel A and real underwater wireless acoustic channel estimated during SPACE08 measurements to verify the selection.
APA, Harvard, Vancouver, ISO, and other styles
5

Strobel, Matthias. "Estimation of minimum mean squared error with variable metric from censored observations." [S.l. : s.n.], 2008. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-35333.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Alexandridis, Roxana Antoanela. "Minimum disparity inference for discrete ranked set sampling data." Connect to resource, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1126033164.

Full text
Abstract:
Thesis (Ph. D.)--Ohio State University, 2005.
Title from first page of PDF file. Document formatted into pages; contains xi, 124 p.; also includes graphics. Includes bibliographical references (p. 121-124). Available online via OhioLINK's ETD Center
APA, Harvard, Vancouver, ISO, and other styles
7

Williams, Ian E. "Channel Equalization and Spatial Diversity for Aeronautical Telemetry Applications." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/605946.

Full text
Abstract:
ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California
This work explores aeronautical telemetry communication performance with the SOQPSK- TG ARTM waveforms when frequency-selective multipath corrupts received information symbols. A multi-antenna equalization scheme is presented where each antenna's unique multipath channel is equalized using a pilot-aided optimal linear minimum mean-square error filter. Following independent channel equalization, a maximal ratio combining technique is used to generate a single receiver output for detection. This multi-antenna equalization process is shown to improve detection performance over maximal ratio combining alone.
APA, Harvard, Vancouver, ISO, and other styles
8

Kulkarni, Aditya. "Performance Analysis of Zero Forcing and Minimum Mean Square Error Equalizers on Multiple Input Multiple Output System on a Spinning Vehicle." International Foundation for Telemetering, 2014. http://hdl.handle.net/10150/577482.

Full text
Abstract:
ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA
Channel equalizers based on minimum mean square error (MMSE) and zero forcing (ZF) criteria have been formulated for a general scalable multiple input multiple output (MIMO) system and implemented for a 2x2 MIMO system with spatial multiplexing (SM) for Rayleigh channel associated with additive white Gaussian noise. A model to emulate transmitters and receivers on a spinning vehicle has been developed. A transceiver based on the BLAST architecture is developed in this work. A mathematical framework to explain the behavior of the ZF and MMSE equalizers is formulated. The performance of the equalizers has been validated for a case with one of the communication entities being a spinning aero vehicle. Performance analysis with respect to variation of angular separation between the antennas and relative antenna gain for each case is presented. Based on the simulation results a setup with optimal design parameters for placement of antennas, choice of the equalizers and transmit power is proposed.
APA, Harvard, Vancouver, ISO, and other styles
9

Garcia-Alis, Daniel. "On adaptive MMSE receiver strategies for TD-CDMA." Thesis, University of Strathclyde, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366896.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Karaer, Arzu. "Optimum bit-by-bit power allocation for minimum distortion transmission." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4760.

Full text
Abstract:
In this thesis, bit-by-bit power allocation in order to minimize mean-squared error (MSE) distortion of a basic communication system is studied. This communication system consists of a quantizer. There may or may not be a channel encoder and a Binary Phase Shift Keying (BPSK) modulator. In the quantizer, natural binary mapping is made. First, the case where there is no channel coding is considered. In the uncoded case, hard decision decoding is done at the receiver. It is seen that errors that occur in the more significant information bits contribute more to the distortion than less significant bits. For the uncoded case, the optimum power profile for each bit is determined analytically and through computer-based optimization methods like differential evolution. For low signal-to-noise ratio (SNR), the less significant bits are allocated negligible power compared to the more significant bits. For high SNRs, it is seen that the optimum bit-by-bit power allocation gives constant MSE gain in dB over the uniform power allocation. Second, the coded case is considered. Linear block codes like (3,2), (4,3) and (5,4) single parity check codes and (7,4) Hamming codes are used and soft-decision decoding is done at the receiver. Approximate expressions for the MSE are considered in order to find a near-optimum power profile for the coded case. The optimization is done through a computer-based optimization method (differential evolution). For a simple code like (7,4) Hamming code simulations show that up to 3 dB MSE gain can be obtained by changing the power allocation on the information and parity bits. A systematic method to find the power profile for linear block codes is also introduced given the knowledge of input-output weight enumerating function of the code. The information bits have the same power, and parity bits have the same power, and the two power levels can be different.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Minimum mean square error"

1

Clements, Michael P. On the limitations of comparing mean square forecast error. Oxford: Oxford University, Institute of Economics and Statistics, 1992.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

G, Kalit, and Ames Research Center, eds. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Baram, Yoram. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

G, Kalit, and Ames Research Center, eds. Mean-square error bounds for reduced-order linear state estimators. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1987.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Hoque, Asraul. The exact multiperiod mean-square forecast error for the first-order autoregressive model. London: London School of Economics, 1986.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Magnus, Jan R. The exact multiperiod mean-square forecast error for the first-order autoregressive modelwith an intercept. London: National Institute of Economic and Social Research, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Magnus, Jan R. The exact multiperiod mean-square forecast error for the first-order autoregressive model with an intercept. London: International Centre for Economics and Related Disciplines, 1988.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
8

Cardot, Hervé, and Pascal Sarda. Functional Linear Regression. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.

Full text
Abstract:
This article presents a selected bibliography on functional linear regression (FLR) and highlights the key contributions from both applied and theoretical points of view. It first defines FLR in the case of a scalar response and shows how its modelization can also be extended to the case of a functional response. It then considers two kinds of estimation procedures for this slope parameter: projection-based estimators in which regularization is performed through dimension reduction, such as functional principal component regression, and penalized least squares estimators that take into account a penalized least squares minimization problem. The article proceeds by discussing the main asymptotic properties separating results on mean square prediction error and results on L2 estimation error. It also describes some related models, including generalized functional linear models and FLR on quantiles, and concludes with a complementary bibliography and some open problems.
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Minimum mean square error"

1

Weik, Martin H. "minimum mean-square error filtering." In Computer Science and Communications Dictionary, 1022. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11569.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Weik, Martin H. "minimum mean-square error restoration." In Computer Science and Communications Dictionary, 1022. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11570.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Jansen, Maarten. "The minimum mean squared error threshold." In Noise Reduction by Wavelet Thresholding, 47–79. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0145-5_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Deng, Chengzhi. "Minimum Mean Square Error Estimator for Shearlet Coefficients Reconstruction." In Lecture Notes in Electrical Engineering, 737–44. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-2169-2_88.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Martinek, Radek, George Razera, Radana Kahankova, and Jan Žídek. "Optimization of the Training Symbols for Minimum Mean Square Error Equalizer." In Proceedings of the Third International Afro-European Conference for Industrial Advancement — AECIA 2016, 272–87. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60834-1_28.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Lee, Jungsik, and Ravi Sankar. "Theoretical Derivation of Minimum Mean Square Error of RBF Based Equalizer." In Lecture Notes in Computer Science, 293–302. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11881070_43.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Devroye, Luc, Paola G. Ferrario, László Györfi, and Harro Walk. "Strong Universal Consistent Estimate of the Minimum Mean Squared Error." In Empirical Inference, 143–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41136-6_14.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

He, Hong, Xin Yin, Tong Yang, and Lin He. "Based on the of FFT Algorithm the Minimum Mean Square Error Linear Equilibrium Algorithm." In Advances in Intelligent and Soft Computing, 591–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30126-1_93.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Homenda, Wladyslaw, and Tomasz Penza. "Mapping Points Back from the Concept Space with Minimum Mean Squared Error." In Computer Information Systems and Industrial Management, 67–78. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45378-1_7.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Awasthi, Neha, and Sukesha Sharma. "Comparative Analysis of Least Square, Minimum Mean Square Error and KALMAN Estimator Using DWT (Discrete Wavelet Transform)-Based MIMO-OFDM System." In Advances in Intelligent Systems and Computing, 233–41. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8618-3_25.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Minimum mean square error"

1

Ephraim, Y. "On minimum mean square error speech enhancement." In [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1991. http://dx.doi.org/10.1109/icassp.1991.150509.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Hua Peng and Naofal Al-Dhahir. "Sparse minimum mean square error(MMSE) blind beamformer." In 2015 IEEE International Wireless Symposium (IWS). IEEE, 2015. http://dx.doi.org/10.1109/ieee-iws.2015.7164517.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Tsai, Fu Y., and Huei Peng. "Minimum mean square error linear predictor with rounding." In Visual Communications and Image Processing '95, edited by Lance T. Wu. SPIE, 1995. http://dx.doi.org/10.1117/12.206750.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Jia, G. Q., Y. Pan, J. J. Du, and X. H. Ji. "Symbol detection aided minimum mean square error interference alignment." In 2018 IEEE MTT-S International Wireless Symposium (IWS). IEEE, 2018. http://dx.doi.org/10.1109/ieee-iws.2018.8400860.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Kock, Markus, Steffen Busch, and Holger Blume. "Hardware accelerator for minimum mean square error interference alignment." In 2015 IEEE International Conference on Digital Signal Processing (DSP). IEEE, 2015. http://dx.doi.org/10.1109/icdsp.2015.7251939.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Park, Stephen K., and Stephen E. Reichenbach. "Digital image gathering and minimum mean-square error restoration." In Lausanne - DL tentative, edited by Murat Kunt. SPIE, 1990. http://dx.doi.org/10.1117/12.24172.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Petra, N., D. De Caro, A. G. M. Strollo, V. Garofalo, E. Napoli, M. Coppola, and P. Todisco. "Fixed-width CSD multipliers with minimum mean square error." In 2010 IEEE International Symposium on Circuits and Systems - ISCAS 2010. IEEE, 2010. http://dx.doi.org/10.1109/iscas.2010.5537606.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Sadeghi, Parastoo, Rodney A. Kennedy, and Zubair Khalid. "Minimum mean square error equalization on the 2-sphere." In 2014 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2014. http://dx.doi.org/10.1109/ssp.2014.6884585.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

LeBlanc, J. P., and S. W. McLaughlin. "Minimum mean square error channel truncation for magnetic channels." In IEEE International Magnetics Conference. IEEE, 1999. http://dx.doi.org/10.1109/intmag.1999.837821.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Petra, Nicola, Davide De Caro, and Antonio G. M. Strollo. "Design of fixed-width multipliers with minimum mean square error." In 2007 European Conference on Circuit Theory and Design (ECCTD 2007). IEEE, 2007. http://dx.doi.org/10.1109/ecctd.2007.4529633.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Minimum mean square error"

1

Sun, Winston Y. Linear adaptive noise-reduction filters for tomographic imaging: Optimizing for minimum mean square error. Office of Scientific and Technical Information (OSTI), April 1993. http://dx.doi.org/10.2172/10148667.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Bruder, Brittany L., Katherine L. Brodie, Tyler J. Hesser, Nicholas J. Spore, Matthew W. Farthing, and Alexander D. Renaud. guiBath y : A Graphical User Interface to Estimate Nearshore Bathymetry from Hovering Unmanned Aerial System Imagery. Engineer Research and Development Center (U.S.), February 2021. http://dx.doi.org/10.21079/11681/39700.

Full text
Abstract:
This US Army Engineer Research and Development Center, Coastal and Hydraulics Laboratory, technical report details guiBathy, a graphical user interface to estimate nearshore bathymetry from imagery collected via a hovering Unmanned Aerial System (UAS). guiBathy provides an end-to-end solution for non-subject-matter-experts to utilize commercia-off-the-shelf UAS to collect quantitative imagery of the nearshore by packaging robust photogrammetric and signal-processing algorithms into an easy-to-use software interface. This report begins by providing brief background on coastal imaging and the photogrammetry and bathymetric inversion algorithms guiBathy utilizes, as well as UAS data collection requirements. The report then describes guiBathy software specifications, features, and workflow. Example guiBathy applications conclude the report with UAS bathymetry measurements taken during the 2020 Atlantic Hurricane Season, which compare favorably (root mean square error = 0.44 to 0.72 m; bias = -0.35 to -0.11 m) with in situ survey measurements. guiBathy is a standalone executable software for Windows 10 platforms and will be freely available at www.github.com/erdc.
APA, Harvard, Vancouver, ISO, and other styles
3

Pradhan, Nawa Raj. Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region, USA. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42128.

Full text
Abstract:
A soil moisture retrieval method is proposed, in the absence of ground-based auxiliary measurements, by deriving the soil moisture content relationship from the satellite vegetation index-based evapotranspiration fraction and soil moisture physical properties of a soil type. A temperature–vegetation dryness index threshold value is also proposed to identify water bodies and underlying saturated areas. Verification of the retrieved growing season soil moisture was performed by comparative analysis of soil moisture obtained by observed conventional in situ point measurements at the 239-km2 Reynolds Creek Experimental Watershed, Idaho, USA (2006–2009), and at the US Climate Reference Network (USCRN) soil moisture measurement sites in Sundance, Wyoming (2012–2015), and Lewistown, Montana (2014–2015). The proposed method best represented the effective root zone soil moisture condition, at a depth between 50 and 100 cm, with an overall average R2 value of 0.72 and average root mean square error (RMSE) of 0.042.
APA, Harvard, Vancouver, ISO, and other styles
4

Al-Qadi, Imad, Qingqing Cao, Lama Abufares, Siqi Wang, Uthman Mohamed Ali, and Greg Renshaw. Moisture Content and In-place Density of Cold-Recycling Treatments. Illinois Center for Transportation, May 2022. http://dx.doi.org/10.36501/0197-9191/22-007.

Full text
Abstract:
Cold-recycling treatments are gaining popularity in the United States because of their economic and environmental benefits. Curing is the most critical phase for these treatments. Curing is the process where emulsion breaks and water evaporates, leaving residual binder in the treated material. In this process, the cold-recycled mix gains strength. Sufficient strength is required before opening the cold-treated layer to traffic or placing an overlay. Otherwise, premature failure, related to insufficient strength and trapped moisture, would be expected. However, some challenges arise from the lack of relevant information and specifications to monitor treatment curing. This report presents the outcomes of a research project funded by the Illinois Department for Transportation to investigate the feasibility of using the nondestructive ground-penetrating radar (GPR) for density and moisture content estimation of cold-recycled treatments. Monitoring moisture content is an indicator of curing level; treated layers must meet a threshold of maximum allowable moisture content (2% in Illinois) to be considered sufficiently cured. The methodology followed in this report included GPR numerical simulations and GPR indoor and field tests for data sources. The data were used to correlate moisture content to dielectric properties calculated from GPR measurements. Two models were developed for moisture content estimation: the first is based on numerical simulations and the second is based on electromagnetic mixing theory and called the Al-Qadi-Cao-Abufares (ACA) model. The simulation model had an average error of 0.33% for moisture prediction for five different field projects. The ACA model had an average error of 2% for density prediction and an average root-mean-square error of less than 0.5% for moisture content prediction for both indoor and field tests. The ACA model is presented as part of a developed user-friendly tool that could be used in the future to continuously monitor curing of cold-recycled treatments.
APA, Harvard, Vancouver, ISO, and other styles
5

Brodie, Katherine, Brittany Bruder, Richard Slocum, and Nicholas Spore. Simultaneous mapping of coastal topography and bathymetry from a lightweight multicamera UAS. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41440.

Full text
Abstract:
A low-cost multicamera Unmanned Aircraft System (UAS) is used to simultaneously estimate open-coast topography and bathymetry from a single longitudinal coastal flight. The UAS combines nadir and oblique imagery to create a wide field of view (FOV), which enables collection of mobile, long dwell timeseries of the littoral zone suitable for structure-from motion (SfM), and wave speed inversion algorithms. Resultant digital surface models (DSMs) compare well with terrestrial topographic lidar and bathymetric survey data at Duck, NC, USA, with root-mean-square error (RMSE)/bias of 0.26/–0.05 and 0.34/–0.05 m, respectively. Bathymetric data from another flight at Virginia Beach, VA, USA, demonstrates successful comparison (RMSE/bias of 0.17/0.06 m) in a secondary environment. UAS-derived engineering data products, total volume profiles and shoreline position, were congruent with those calculated from traditional topo-bathymetric surveys at Duck. Capturing both topography and bathymetry within a single flight, the presented multicamera system is more efficient than data acquisition with a single camera UAS; this advantage grows for longer stretches of coastline (10 km). Efficiency increases further with an on-board Global Navigation Satellite System–Inertial Navigation System (GNSS-INS) to eliminate ground control point (GCP) placement. The Appendix reprocesses the Virginia Beach flight with the GNSS–INS input and no GCPs.
APA, Harvard, Vancouver, ISO, and other styles
6

Collins, Clarence O., and Tyler J. Hesser. altWIZ : A System for Satellite Radar Altimeter Evaluation of Modeled Wave Heights. Engineer Research and Development Center (U.S.), February 2021. http://dx.doi.org/10.21079/11681/39699.

Full text
Abstract:
This Coastal and Hydraulics Engineering Technical Note (CHETN) describes the design and implementation of a wave model evaluation system, altWIZ, which uses wave height observations from operational satellite radar altimeters. The altWIZ system utilizes two recently released altimeter databases: Ribal and Young (2019) and European Space Agency Sea State Climate Change Initiative v.1.1 level 2 (Dodet et al. 2020). The system facilitates model evaluation against 1 Hz1 altimeter data or a product created by averaging altimeter data in space and time around model grid points. The system allows, for the first time, quantitative analysis of spatial model errors within the U.S. Army Corps of Engineers (USACE) Wave Information Study (WIS) 30+ year hindcast for coastal United States. The system is demonstrated on the WIS 2017 Atlantic hindcast, using a 1/2° basin scale grid and a 1/4° regional grid of the East Coast. Consistent spatial patterns of increased bias and root-mean-square-error are exposed. Seasonal strengthening and weakening of these spatial patterns are found, related to the seasonal variation of wave energy. Some model errors correspond to areas known for high currents, and thus wave-current interaction. In conjunction with the model comparison, additional functions for pairing altimeter measurements with buoy data and storm tracks have been built. Appendices give information on the code access (Appendix I), organization and files (Appendix II), example usage (Appendix III), and demonstrating options (Appendix IV).
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Minimum mean square error' for particular source types:
Journal articles Dissertations / Theses
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography