Relevant bibliographies by topics / Multiple output

Academic literature on the topic 'Multiple output'

Author: Grafiati
Published: 4 June 2021
Last updated: 21 February 2023

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Journal articles on the topic "Multiple output"

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Kang, Byung-Soo, Ji-Hoon Bae, Eun-Jung Yang, and Kyung-Tae Kim. "3-D Multiple-Input Multiple-Output Interferometric ISAR Imaging." Journal of Korean Institute of Electromagnetic Engineering and Science 26, no. 6 (June 30, 2015): 564–71. http://dx.doi.org/10.5515/kjkiees.2015.26.6.564.

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Fernández, Carmen, Gary Koop, and Mark F. J. Steel. "Multiple-Output Production With Undesirable Outputs." Journal of the American Statistical Association 97, no. 458 (June 2002): 432–42. http://dx.doi.org/10.1198/016214502760046989.

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Smallwood, David O. "Multiple-Input Multiple-Output (MIMO) Linear Systems Extreme Inputs/Outputs." Shock and Vibration 14, no. 2 (2007): 107–31. http://dx.doi.org/10.1155/2007/701837.

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A linear structure is excited at multiple points with a stationary normal random process. The response of the structure is measured at multiple outputs. If the autospectral densities of the inputs are specified, the phase relationships between the inputs are derived that will minimize or maximize the trace of the autospectral density matrix of the outputs. If the autospectral densities of the outputs are specified, the phase relationships between the outputs that will minimize or maximize the trace of the input autospectral density matrix are derived. It is shown that other phase relationships and ordinary coherence less than one will result in a trace intermediate between these extremes. Least favorable response and some classes of critical response are special cases of the development. It is shown that the derivation for stationary random waveforms can also be applied to nonstationary random, transients, and deterministic waveforms.
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Yuanquan Wang, Yuanquan Wang, and Nan Chi Nan Chi. "Indoor gigabit 2 × 2 imaging multiple-input–multiple-output visible light communication." Chinese Optics Letters 12, no. 10 (2014): 100603–6. http://dx.doi.org/10.3788/col201412.100603.

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Grip, Håvard Fjær, Ali Saberi, and Xu Wang. "Stabilization of Multiple-Input Multiple-Output Linear Systems With Saturated Outputs $ $." IEEE Transactions on Automatic Control 55, no. 9 (September 2010): 2160–64. http://dx.doi.org/10.1109/tac.2010.2051250.

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Mizumoto, Ikuro, Seiya Fujii, and Hiroshi Mita. "Output Feedback-Based Output Tracking Control with Adaptive Output Predictive Feedforward for Multiple-Input–Multiple-Output Systems." Industrial & Engineering Chemistry Research 58, no. 26 (February 18, 2019): 11382–91. http://dx.doi.org/10.1021/acs.iecr.9b00107.

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Smallwood, David. "Minimum Input Trace for Multiple Input Multiple Output Linear Systems." Journal of the IEST 56, no. 2 (October 1, 2013): 57–67. http://dx.doi.org/10.17764/jiet.56.2.41344333010617q6.

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Specification of the cross spectra for a multiple-input/multiple-output (MIMO) vibration test is challenging. This paper presents a method for tests where the specifications of the output (the control points) autospectra are available. The autospectra of the outputs are specified and cross spectra between the outputs are derived that will minimize the trace of the autospectra of the inputs (the drive signals) with the constraint that the input spectral density matrix is positive definite. The hypothesis is that nature likes a minimum energy solution.
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Lauwers, Oliver, Oscar Mauricio Agudelo, and Bart De Moor. "A Multiple-Input Multiple-Output Cepstrum." IEEE Control Systems Letters 2, no. 2 (April 2018): 272–77. http://dx.doi.org/10.1109/lcsys.2018.2828992.

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Laurı́, D., J. V. Salcedo, M. Martı́nez, and S. Garcı́a-Nieto. "Model predictive control relevant identification: multiple input multiple output against multiple input single output." IET Control Theory & Applications 4, no. 9 (September 1, 2010): 1756–66. http://dx.doi.org/10.1049/iet-cta.2009.0482.

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Shanmugam, Kirubanandan. "System Identification and Characteristics of Multiple Input and Multiple Output (MIMO) Water Mixing Equipment." BOHR International Journal of Engineering 1, no. 1 (2022): 30–34. http://dx.doi.org/10.54646/bije.006.

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Multiple input and multiple output (MIMO) water mixing equipment is a prototype used to study the process control concepts. This equipment is used for manipulating multiple inputs and their effect on the outputs. The input variables are hot water (HW) temperature, cold water (CW) temperature, and flow rate of HW and CW. The output variables are the level of the water in the tank, the temperature of the water, and the flow of outlet water. The changes in controlled variables with the effect of manipulated variables were investigated. The transfer function for the given experimental setup was developed and the time constant for the given system was also developed. These transfer function and analysis of MIMO can be useful for the analysis of various MIMO-based process equipments.
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Dissertations / Theses on the topic "Multiple output"

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Kanday, Balaji Madapuci. "Microcontroller Based Multiple-Input Multiple-Output Transmitter." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/605952.

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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 paper describes how a microcontroller based system can be used to generate the signals needed in a multiple-input multiple-output (MIMO) system transmitter. The limited computational speed of the microcontroller, along with other tasks which the controller may need to handle, places limits on the throughput of the system, and the complexity of the MIMO signal design. However this can be a low cost design, and the microcontroller can be used to perform other operations in the system, which may make it attractive in some applications.
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Tran, Tuan-Anh. "Multiple-input multiple-output optical wireless communications." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:094fbe23-88c3-49c4-b64b-a1de40674123.

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Visible-light optical wireless communications (OWC) is a potential technology that can help resolve the crowdedness of the radio-frequency bands, whilst conveniently exploiting energy-saving light-emitting diodes (LEDs) as transmitters for both illumination and communications. Since there usually are many LEDs in a lighting unit, OWC has a multi- input multi-output (MIMO) geometry which, thanks to its channel diversity, can offer wireless local networks at data-rates many times higher than possible with single-channel systems. In such systems, MIMO-detection methods to separate the different optical channels play an important role in improving the system performance by helping reduce cross-talk between channels. To measure the performance of a particular geometry for MIMO communications, a simulation study, reported in this thesis, found that, amongst the signal- independent metrics, the condition number may be used as a rough predictor of the performance, whilst the channel Signal-to-Interference-and-Noise Ratio (SINR) is the most appropriate for geometry assessment. Combined with the fact that the overall performance of a MIMO system is mostly dominated by its worst channel, this indicates that the most effective way to improve the system performance is to maximise the worst channel’s SINR. One of the possible solutions to improving the SINRs is to use holograms to steer the transmitter images such that their distributions over the photo-detectors reduce overlaps. As LEDs emit partially-coherent light, the beam steering has to be carried out with partially- coherent illumination. By using two lenses to parallelise and collect partially-coherent light before and after the hologram, respectively, the source and image intensity distributions, and the autocorrelation of the hologram can be related in a succinct mathematical relationship. This leads to the development of three computational algorithms based on the autocorrelation function to obtain a quantised hologram with the desired beam-steering capability. These algorithms have their cost functions and performance comparison done at the hologram plane instead of the image plane, which therefore takes less time than traditional image-based methods. Specifically, one of these algorithms is able to save significant time over both the other autocorrelation-based algorithms and the direct binary-search, by 33% and by 50% respectively. A simulation-based study and a corresponding experiment, both reported in this thesis, found that the one of the proposed algorithms had poor power efficiency, whilst the other two were both highly effective in generating digital holograms with precise and power-efficient beam-steering performance. Of these two algorithms, one had superior time performance and was likely the best of the three proposed autocorrelation-based algorithms for generating beam-steering holograms. MIMO-OWC simulation also demonstrated the capability of using beam-steering holograms to design the channel and improve the system performance. Combining reported findings, a strategy can be devised to optimise the throughput of an imaging MIMO-OWC system for a given transmitted power.
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Petersen, Samuel. "Multiple-Input Multiple-Output Systems for Spinning Vehicles." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/605956.

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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 paper investigates the performance of a multiple-input multiple-output (MIMO) digital communication system, when the transmitter is located on a spinning vehicle. In particular, a 2x2 MIMO system is used, with Alamouti coding at the transmitter. Both Rayleigh and Rayleigh plus line-of-sight, or Rician, models combined with a deterministic model to simulate the channel. The spinning of the transmitting vehicle, relative to the stationary receive antennas, modulates the signal, and complicates the decoding and channel parameter estimation processes. The simulated system bit error rate is the primary performance metric used. The Alamouti channel code is shown to perform better than the maximal ratio receiver combining (MRRC) and single receiver (2x1) system in some circumstances and performs similarly to the MRRC in the broadside case.
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Zhang, Peichang. "Coherent versus differential multiple-input multiple-output systems." Thesis, University of Southampton, 2015. https://eprints.soton.ac.uk/376511/.

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In recent years, Multiple-Input-Multiple-Output (MIMO) techniques have attracted substantial attention due to their capability of providing spatial diversity and/or multiplexing gains. Inspired by the concept of Spatial Modulation (SM), the novel concept of Space-Time-Shift-Keying (STSK) was recently proposed, which is considered to have the following advantages: 1) STSK constitutes a generalized shift keying architecture, which is capable of striking the required trade-off between the required spatial and time diversity as well as multiplexing gain and includes SM and Space Shift Keying (SSK) as its special cases. 2) Its high degree of design-freedom, the above-mentioned flexible diversity versus multiplexing gain trade-off can be achieved by optimizing both the number and size of the dispersion matrices, as well as the number of transmit and receive antennas. 3) Similar to the SM/SSK schemes, the Inter-Antenna-Interference (IAI) may be eliminated and consequently, the adoption of single-antenna-based Maximum Likelihood (ML) detection becomes realistic in STSK schemes. In this report, our investigation can be classified into two major categories, Coherent STSK (CSTSK) and Differential STSK (DSTSK) schemes. For CSTSK, since Channel State Information (CSI) is required for data detection, Channel Estimation (CE) techniques become necessary. To be more explicit, we first briefly review the conventional Training Based CE (TBCE) and Semi-Blind CE (SBCE) schemes for the CSTSK MIMO schemes. In addition, we develop a Blockof-Bits Selection Based CE (BBSBCE) algorithm for CSTSK schemes for increasing the overall system’s throughput, while improving the accuracy of the CE. Additionally, it has been widely recognised that MIMO schemes are capable of achieving a diversity and/or multiplexing gain by employing multiple Antenna Elements (AEs) at the transmitter and/or the receiver. However, it should also noted that since MIMO systems utilize multiple RF chains, their power consumption and hardware costs become substantial. Against this background, we introduce the concept of (Antenna Selection) AS and propose a simple yet efficient AS algorithm, namely the Norm-Based Joint Transmit and Receive AS (NBJTRAS) for assisting MIMO systems. For DSTSK, since no CSI is required for differential detection schemes, it also draws our attention. However, in the absence of CE, the Conventional Differential Detection (CDD) schemes usually suffer from a 3 dB performance degradation and may exhibit an error-flow when Doppler frequency is excessive. In order to mitigate this problem, we investigate Multiple-Symbol Differential Sphere Detection (MSDSD) scheme and adopt it in our DSTSK scheme to improve the system performance, while reducing the detection complexity. Furthermore, based on our MSDSD detected DSTSK scheme, we propose a DSTSK aided Multi-User Successive Relaying aided Cooperative System (MUSRC), which is capable of supporting various number of users flexibly, while covering the conventional 50% throughput loss due to the half-duplex transmit and receive constraint of practical transceivers.
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Uppal, Momin Ayub. "Code design for multiple-input multiple-output broadcast channels." [College Station, Tex. : Texas A&M University, 2006. http://hdl.handle.net/1969.1/ETD-TAMU-1783.

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Yu, Kai. "Modeling of Multiple-Input Multiple-Output Radio Propagation Channels." Licentiate thesis, KTH, Signals, Sensors and Systems, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-1478.

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In recent years, multiple-input multiple-output (MIMO)systems appear to be very promising since they can provide highdata rates in environments with sucient scattering byexploiting the spatial domain. To design a real MIMO wirelesssystem and predict its performance under certain circumstances,it is necessary to have accurate MIMO wireless channel modelsfor dierent scenarios. This thesis presents dierent models forindoor MIMO radio propagation channels based on 5.2 GHz indoorMIMO channel measurements.The recent research on MIMO radio channel modeling isbriey reviewed in this thesis. The models are categorized intonon-physical and physical models. The non-physical modelsprimarily rely on the statistical characteristics of MIMOchannels obtained from the measured data while the physicalmodels describe the MIMO channel (or its distribution) via somephysical parameters. The relationships between dierent modelsare also discussed.For the narrowband case, a non line-of-sight (NLOS)indoor MIMO channel model is presented. The model is based on aKronecker structure of the channel covariance matrix and thefact that the channel is complex Gaussian. It is extended tothe line-of-sight (LOS) scenario by estimating and modeling thedominant component separately.As for the wideband case, two NLOS MIMO channel modelsare proposed. The rst model uses the power delay prole and theKronecker structure of the second order moments of each channeltap to model the wideband MIMO channel while the second modelcombines a simple single-input single-output (SISO) model withthe same Kronecker structure of the second order moments.Monte-Carlo simulations are used to generate indoor MIMOchannel realizations according to the above models. The resultsare compared with the measured data and good agreement has beenobserved.

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Dambul, Katrina D. "Multiple-input multiple-output (MIMO) in optical wireless communications." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.558676.

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There is growing demand for indoor wireless communication systems with higher bandwidth and higher data rates. However, the crowded radio frequency (RF) spectrum has caused researchers to consider optical wireless systems. In this thesis, optical signals in the visible region of the spectrum are used. White LEDs are used as transmitters as they provide higher signal-to-noise (SNR) levels and a better link budget than the infrared alternative. Typical modulation bandwidths for white LEDs are limited to tens of MHz. Thus, multiple-input multiple-output (MIMO) transmission is considered as a means to increase data rate. The development of the indoor optical wireless MIMO system begins with the geometrical and mathematical analysis of a single-input single-output (SISO) system and a single-input multiple- output (SIMO) system. The same analysis is then performed for a MIMO system. For the MIMO system, an experimental demonstration using white LEDs and non-imaging receivers are reported. Results include coverage measurements and an SNR analysis. There are limitations using non- imaging receivers, such as coverage limitations and symmetry problems, which cause problem with signal recovery. To improve these limitations, imaging receivers are considered. The design and development of an experimental demonstration of an indoor optical wireless MIMO system with an imaging receiver is presented. The experimental setup consists of a transmitter with a 2 x 2 array of white LEDs and a receiver with a 3 x 3 photo detector array. The system transmits data at a bit rate of 2Mbit/s/channel. Detailed design specifications and optical design are presented. Results show that certain positions within the system coverage area have error-free operation. The BER and SNR analysis shows that the overall BER improves with the overall SNR. In order to exploit the full potential of the system, future work should focus on improving the SNR and BER of the system.
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Gupte, Abhishek. "SOQPSK Signals in Multiple Input Multiple Output (MIMO) Systems." International Foundation for Telemetering, 2010. http://hdl.handle.net/10150/605954.

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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 paper investigates the use of shaped offset quadrature phase shift keying (SOQPSK) signals in multiple-input multiple-output (MIMO) communication systems. The goal is to integrate commonly used receiver architectures for conventional single-input single-output (SISO) systems into a corresponding MIMO system. The benefits of improved spectral efficiency are juxtaposed against the increased receiver complexity. Bit error rate performances for the SISO and MIMO architectures in a multipath environment are compared and conclusions regarding trade-offs between signal to noise ratio (SNR) and spectral efficiency stated.
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Stewart, Kyle Bradley. "Waveform-Diverse Multiple-Input Multiple-Output Radar Imaging Measurements." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1450437383.

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Najam, Ali Imran. "Multiple-input multiple-output antennas for ultra wideband communications." Grenoble INPG, 2010. http://www.theses.fr/2010INPG0043.

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La radio Ultra Large Bande (ULB) promet de nouveaux marchés dans les domaines des réseaux personnels hauts débits et de capteurs. De sorte à améliorer la robustesse du lien radio et le débit, l’association des techniques MIMO à l’ULB a été envisagée. En vue d’une réalisation pratique, un challenge fondamental reste la conception des antennes qui doivent répondre aux contraintes de l’ULB et des systèmes multi-antennaires, et aux contraintes physiques et économiques. Dans ce contexte, plusieurs nouveaux designs d’antennes MIMO ULB sont proposés. Leur caractérisation s’appuie sur les paramètres conventionnels utilisés en conception d’antennes ainsi que des paramètres spécifiques à l’ULB et au MIMO. En particulier, un nouveau design compact présentant une forte isolation grâce à l’insertion d’un stub sur le plan de masse est proposé. Une nouvelle méthode de modélisation du couplage mutuel, qui présente l’avantage d’offrir de nouvelles approches pour le compenser, est également introduite
UWB technology has rapidly emerged in the areas of WPAN and sensors networks featuring high data rate communications. The applications of UWB are limited to very short-range communications due to the extremely low transmitted power. The combination of MIMO techniques with UWB has been considered as a solution to improve the range. However, a fundamental challenge arises for the design of antennas that faces the constraints offered by UWB systems and multi-antennas systems, and the constraints of size and cost. In this context, several new UWB-MIMO antennas are proposed. Their characterization is based on the parameters relevant to conventional antenna design and the specific parameters relevant to the UWB-MIMO antenna design. In particular, a new compact design with high isolation by inserting the inverted-Y shaped stub on the ground plane is proposed. A new method for modelling the mutual coupling, is also introduced which has the advantage of offering new approach to compensate it
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Books on the topic "Multiple output"

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Costa, Nelson, and Simon Haykin. Multiple-Input, Multiple-Output Channel Models. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470590676.

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Costa, Nelson. Multiple-input multiple-output channel models: Theory and practice. Hoboken, N.J: Wiley, 2010.

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Costa, Nelson. Multiple-input multiple-output channel models: Theory and practice. Hoboken, N.J: Wiley, 2010.

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Burken, John J. Flight-determined stability analysis of multiple-input-multiple-output control systems. Edwards, Calif: Dryden Flight Research Facility, 1992.

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Glass, J. C. The achievement of scale efficiency in UK universities: A multiple-input multiple-output analysis. [Belfast]: Accounting and Finance Division, School of Finance and Information, Queen's University of Belfast, 1994.

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Lang, Zi-Qiang. Evaluation of output frequency responses of nonlinear systems under multiple inputs. Sheffield: Univeristy of Sheffield, Dept. of Automatic Control and Systems Engineering, 1997.

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Wall, Charles A. Modelling a multiple output production system: Supply response in the Australian sheep industry. [Sydney]: University of Sydney, Dept. of Agricultural Economics, 1987.

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Sinha, Anushree. Developing state level input-output tables: Multiplier analysis for Karnataka, Uttarakhand, and Jharkhand. New Delhi: National Council of Applied Economic Research, 2009.

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Pyatt, Frank Graham. The method of apportionment and its application to multiplier models. Coventry: University of Warwick, Development Economics Research Centre, 1988.

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Statistics, Alberta Bureau of. Economic multipliers for Alberta industries and commodities: (based on 1984 input-output tables). Edmonton, Alta: Alberta Bureau of Statistics, Alberta Treasury, 1991.

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Book chapters on the topic "Multiple output"

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Yang, Ruliang, Haiying Li, Shiqiang Li, Ping Zhang, Lulu Tan, Xiangwu Gao, and Xueyan Kang. "Multiple-Input Multiple-Output SAR." In High-Resolution Microwave Imaging, 387–406. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-7138-6_12.

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Escalera, Sergio, Oriol Pujol, and Petia Radeva. "Recoding Error-Correcting Output Codes." In Multiple Classifier Systems, 11–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02326-2_2.

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Kumar, Sanjay. "Multiple Input Multiple Output (MIMO) Systems." In Wireless Communication-the fundamental and advanced concepts, 613–50. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003340058-21.

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Jan, Yasir, Ferdous Sohel, Mohd Fairuz Shiratuddin, and Kok Wai Wong. "MON: Multiple Output Neurons." In Communications in Computer and Information Science, 432–39. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36802-9_46.

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Christensen, Stefan W. "Ensemble Construction via Designed Output Distortion." In Multiple Classifier Systems, 286–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44938-8_29.

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Leung Lee, Albert Ting, Weijian Jin, Siew-Chong Tan, and Ron Shu Yuen Hui. "Single-Inductor Multiple-Output DC-DC Converters." In Single-Inductor Multiple-Output Converters, 25–63. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003239833-2.

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Leung Lee, Albert Ting, Weijian Jin, Siew-Chong Tan, and Ron Shu Yuen Hui. "Single-Inductor Multiple-Output DC-AC Buck-Boost Inverters." In Single-Inductor Multiple-Output Converters, 159–97. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003239833-5.

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Leung Lee, Albert Ting, Weijian Jin, Siew-Chong Tan, and Ron Shu Yuen Hui. "Single-Inductor Multiple-Output AC-DC Converters." In Single-Inductor Multiple-Output Converters, 65–113. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003239833-3.

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Leung Lee, Albert Ting, Weijian Jin, Siew-Chong Tan, and Ron Shu Yuen Hui. "Single-Inductor Multiple-Output DC-AC Boost Inverters." In Single-Inductor Multiple-Output Converters, 115–57. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003239833-4.

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Leung Lee, Albert Ting, Weijian Jin, Siew-Chong Tan, and Ron Shu Yuen Hui. "Gallium Nitride-Based Single-Inductor Multiple-Output DC-AC Boost Inverters." In Single-Inductor Multiple-Output Converters, 199–252. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003239833-6.

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Conference papers on the topic "Multiple output"

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Agrawal, P., V. D. Agrawal, and N. N. Biswas. "Multiple Output Minimization." In 22nd ACM/IEEE Design Automation Conference. IEEE, 1985. http://dx.doi.org/10.1109/dac.1985.1586015.

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Agrawal, Prathima, Vishwani D. Agrawal, and Nripendra N. Biswas. "Multiple output minimization." In the 22nd ACM/IEEE conference. New York, New York, USA: ACM Press, 1985. http://dx.doi.org/10.1145/317825.317962.

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Ponce, Octavio, Tobias Rommel, Marwan Younis, Pau Prats, and Alberto Moreira. "Multiple-input multiple-output circular SAR." In 2014 15th International Radar Symposium (IRS). IEEE, 2014. http://dx.doi.org/10.1109/irs.2014.6869262.

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Frasca, Marco, and Alfonso Farina. "Multiple Input-Multiple Output Quantum Radar." In 2020 IEEE Radar Conference (RadarConf20). IEEE, 2020. http://dx.doi.org/10.1109/radarconf2043947.2020.9266594.

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Ochs, Julian, Zuardin Akbar, and Philipp Eversmann. "Additive Manufacturing with Solid Wood: Continuous robotic laying of multiple wicker filaments through micro lamination." In Design Computation Input/Output 2020. Design Computation Ltd., 2020. http://dx.doi.org/10.47330/dcio.2020.jzan7781.

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Ren, Xiaoyong, Qiang Zhang, Zhenjin Pang, Qianhong Chen, and Xinbo Ruan. "Input-series output-parallel multiple output converter." In 2014 IEEE Applied Power Electronics Conference and Exposition - APEC 2014. IEEE, 2014. http://dx.doi.org/10.1109/apec.2014.6803774.

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Wurth, Bernd, Klaus Eckl, and Kurt Antreich. "Functional multiple-output decomposition." In the 32nd ACM/IEEE conference. New York, New York, USA: ACM Press, 1995. http://dx.doi.org/10.1145/217474.217506.

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Lake, Don W. "Multiple Output Photodiode Arrays." In 33rd Annual Techincal Symposium, edited by Gary L. Stradling. SPIE, 1990. http://dx.doi.org/10.1117/12.962405.

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Kaskouta, Elpida, Themis Kamilaris, Roman Sotner, Jan Jerabek, and Costas Psychalinos. "Single- Input Multiple-Output and Multiple-Input Single-Output Fractional-Order Filter Designs." In 2018 41st International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2018. http://dx.doi.org/10.1109/tsp.2018.8441348.

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Jiang, Lei, Lars Thiele, Armin Brylka, Stephan Jaeckel, and Volker Jungnickel. "Polarization characteristics of multiple-input multiple-output channels." In 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC). IEEE, 2008. http://dx.doi.org/10.1109/pimrc.2008.4699800.

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Reports on the topic "Multiple output"

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Smallwood, David Ora. Extreme inputs/outputs for multiple input multiple output linear systems. Office of Scientific and Technical Information (OSTI), September 2005. http://dx.doi.org/10.2172/875611.

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Hurdle, Daniel J. Development of Stability/Robustness Considerations for Control System Design with Multiple Input/Multiple Output Plants. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada200408.

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Bernhard, Jennifer T. Enabling Technology for Multiple Input Multiple Output (MIMO) Systems on Mobile Military Platforms: Antennas, Switches, and Packaging. Fort Belvoir, VA: Defense Technical Information Center, May 2011. http://dx.doi.org/10.21236/ada544844.

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Jaffe, Robert. Fractional Representation Design of Dynamic Output Controllers for Multiple Time Scale Systems. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1359.

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R.Lawrece Ives, George Collins, David Marsden Michael Read, Edward Eisen, and Philipp Borchard Takuchi Kamura. A 350 MHz, 200 kW CW, Multiple Beam Inductive Output Tube - Final Report. Office of Scientific and Technical Information (OSTI), November 2012. http://dx.doi.org/10.2172/1055771.

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Sasao, Tsutomu, and Jon T. Butler. A Method to Represent Multiple-Output Switching Functions by Using Multi-Valued Decision Diagrams. Fort Belvoir, VA: Defense Technical Information Center, February 1996. http://dx.doi.org/10.21236/ada605394.

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Whelan, Gene, Karl J. Castleton, John W. Buck, Randal Y. Taira, Gariann M. Gelston, and Dennis L. Strenge. Combining Multiple-Module Output Boundary Conditions to Produce a Single-Input-Module Boundary Condition in FRAMES. Office of Scientific and Technical Information (OSTI), October 2006. http://dx.doi.org/10.2172/894877.

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EdTech Hub, EdTech Hub. Minoritised languages, education, and technology: Current practices and future directions in low- and middle-income countries. EdTech Hub, October 2022. http://dx.doi.org/10.53832/edtechhub.0127.

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This article explores the current status and future directions of minoritised language education and the use of technology in low- and middle-income countries. Our literature review of available academic sources in multiple languages reveals a lack of evidence on the use of technology in minoritised language education across different countries, especially multilingual contexts with greater linguistic diversity. To understand the issue in greater detail and to offer recommendations informed by current practice, we then conducted interviews and a collaborative workshop with four organisations with relevant EdTech initiatives. The analysis covers facilitating and limiting factors these organisations have encountered, as well as the impact of good practice initiatives on learners and society at large. We conclude by identifying the practical, policy, and research properties in the development of minoritised language education and technology. Keywords: minoritised languages, mother tongue, educational technology, LMIC, multilingualism, language of instruction An output of the EdTech Hub, https://edtechhub.org
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Saltus, Christina, Todd Swannack, and S. McKay. Geospatial Suitability Indices Toolbox (GSI Toolbox). Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41881.

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Habitat suitability models are widely adopted in ecosystem management and restoration, where these index models are used to assess environmental impacts and benefits based on the quantity and quality of a given habitat. Many spatially distributed ecological processes require application of suitability models within a geographic information system (GIS). Here, we present a geospatial toolbox for assessing habitat suitability. The Geospatial Suitability Indices (GSI) toolbox was developed in ArcGIS Pro 2.7 using the Python® 3.7 programming language and is available for use on the local desktop in the Windows 10 environment. Two main tools comprise the GSI toolbox. First, the Suitability Index Calculator tool uses thematic or continuous geospatial raster layers to calculate parameter suitability indices based on user-specified habitat relationships. Second, the Overall Suitability Index Calculator combines multiple parameter suitability indices into one overarching index using one or more options, including: arithmetic mean, weighted arithmetic mean, geometric mean, and minimum limiting factor. The resultant output is a raster layer representing habitat suitability values from 0.0 to 1.0, where zero is unsuitable habitat and one is ideal suitability. This report documents the model purpose and development as well as provides a user’s guide for the GSI toolbox.
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Ruosteenoja, Kimmo. Applicability of CMIP6 models for building climate projections for northern Europe. Finnish Meteorological Institute, September 2021. http://dx.doi.org/10.35614/isbn.9789523361416.

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In this report, we have evaluated the performance of nearly 40 global climate models (GCMs) participating in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). The focus is on the northern European area, but the ability to simulate southern European and global climate is discussed as well. Model evaluation was started with a technical control; completely unrealistic values in the GCM output files were identified by seeking the absolute minimum and maximum values. In this stage, one GCM was rejected totally, and furthermore individual output files from two other GCMs. In evaluating the remaining GCMs, the primary tool was the Model Climate Performance Index (MCPI) that combines RMS errors calculated for the different climate variables into one index. The index takes into account both the seasonal and spatial variations in climatological means. Here, MCPI was calculated for the period 1981—2010 by comparing GCM output with the ERA-Interim reanalyses. Climate variables explored in the evaluation were the surface air temperature, precipitation, sea level air pressure and incoming solar radiation at the surface. Besides MCPI, we studied RMS errors in the seasonal course of the spatial means by examining each climate variable separately. Furthermore, the evaluation procedure considered model performance in simulating past trends in the global-mean temperature, the compatibility of future responses to different greenhouse-gas scenarios and the number of available scenario runs. Daily minimum and maximum temperatures were likewise explored in a qualitative sense, but owing to the non-existence of data from multiple GCMs, these variables were not incorporated in the quantitative validation. Four of the 37 GCMs that had passed the initial technical check were regarded as wholly unusable for scenario calculations: in two GCMs the responses to the different greenhouse gas scenarios were contradictory and in two other GCMs data were missing from one of the four key climate variables. Moreover, to reduce inter-GCM dependencies, no more than two variants of any individual GCM were included; this led to an abandonment of one GCM. The remaining 32 GCMs were divided into three quality classes according to the assessed performance. The users of model data can utilize this grading to select a subset of GCMs to be used in elaborating climate projections for Finland or adjacent areas. Annual-mean temperature and precipitation projections for Finland proved to be nearly identical regardless of whether they were derived from the entire ensemble or by ignoring models that had obtained the lowest scores. Solar radiation projections were somewhat more sensitive.
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