Academic literature on the topic 'SIMO systems'

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Journal articles on the topic "SIMO systems"

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Akhilseh, Kumar Verma, Manish, and Rajesh Kumar Dr. "OVERVIEW OF RF COMMUNICATION FROM SISO SYSTEMS TO MIMO SYSTEMS." International Journal of Advances in Engineering & Scientific Research 3, no. 3 (2016): 13–18. https://doi.org/10.5281/zenodo.10752074.

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<strong><em>Abstract: </em></strong> <em>&nbsp;The wireless communication has derived to the present scenario after passing through number of stages and generation. From analog communication of 1<sup>st</sup> generation today we talk about digital communication in 4<sup>th</sup> generation, from the generation of single transmitting antenna and single receive antenna known as SISO systems, we reached the systems with multiple transmitting and multiple receiving antennas known as MIMO systems going through the systems of Multiple Transmit and single receive antenna systems known as MISO systems and Single transmit and multiple receive systems known as SIMO systems. This paper will present a study of generation from SISO systems to MIMO systems for digital communication under the research work going at Banasthali University, Rajsthan, India.Index terms- MIMO, SISO, SIMO, MISO, MMSE, ZFE.</em>
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Akhilseh, Kumar Verma, Manish, and Rajesh Kumar Dr. "EQUALIZATION SCHEMES IN MIMO RF COMMUNICATION: A PERFORMANCE ANALYSIS." International Journal of Advances in Engineering & Scientific Research 3, no. 3 (2016): 44–50. https://doi.org/10.5281/zenodo.10752554.

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<strong><em>Abstract:</em></strong> <strong><em>&nbsp;</em></strong>The wireless communication has derived to the present scenario after passing through number of stages and generation. From analog communication of 1<sup>st</sup> generation today we talk about digital communication in 4<sup>th</sup> generation, from the generation of single transmitting antenna and single receive antenna known as SISO systems, we reached the systems with multiple transmitting and multiple receiving antennas known as MIMO systems going through the systems of Multiple Transmit and single receive antenna systems known as MISO systems and Single transmit and multiple receive systems known as SIMO systems. This paper will present a study of generation from SISO systems to MIMO systems for digital communication under the research work going at Banasthali University, Rajsthan, India. <em>Index terms-</em> MIMO, SISO, SIMO, MISO, MMSE, ZFE.
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Akhilseh, Kumar Verma, Manish, and Rajesh Kumar Dr. "ZFE AND MMSE SCHEMES FOR MIMO COMMUNICATION SYSTEMS : AN ANALYSIS." International Journal of Advances in Engineering & Scientific Research 3, no. 3 (2016): 37–43. https://doi.org/10.5281/zenodo.10752418.

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<strong><em>Abstract:</em></strong> <em>&nbsp;</em>MIMO systems are very important technological advancements with respect to the third generation and fourth generation&rsquo;s wireless networks for RF communication.<em> </em>There are multiple equalization schemes for MIMO systems and two very important of them are ZFE and MMSE. In this paper we are analyzing the performance of both the schemes in different conditions. <em>Index terms-</em> MIMO, SISO, SIMO, MISO, MMSE, ZFE.
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Gang Chen, Jie Chen, and R. Middleton. "Optimal tracking performance for SIMO systems." IEEE Transactions on Automatic Control 47, no. 10 (2002): 1770–75. http://dx.doi.org/10.1109/tac.2002.803559.

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Kim, Young-Gil. "Phase Control of Transmit Antennas in SIMO Systems." Journal of Korea Information and Communications Society 37, no. 8A (2012): 612–17. http://dx.doi.org/10.7840/kics.2012.37a.8.612.

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Kapalin, I. V., and V. V. Fomichev. "Minimal stabilization of vector (MISO and SIMO) systems." Differential Equations 47, no. 11 (2011): 1592–602. http://dx.doi.org/10.1134/s0012266111110061.

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Li, Shuangzhi, Jian-Kang Zhang, and Xiaomin Mu. "Design of Optimal Noncoherent Constellations for SIMO Systems." IEEE Transactions on Communications 67, no. 8 (2019): 5706–20. http://dx.doi.org/10.1109/tcomm.2019.2913367.

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Manolakos, Alexandros, Mainak Chowdhury, and Andrea Goldsmith. "Energy-Based Modulation for Noncoherent Massive SIMO Systems." IEEE Transactions on Wireless Communications 15, no. 11 (2016): 7831–46. http://dx.doi.org/10.1109/twc.2016.2608883.

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An, Ho-jung, and Hyoung-kyu Song. "Cooperative Communication in SIMO Systems with Multiuser-OFDM." IEEE Transactions on Consumer Electronics 53, no. 2 (2007): 339–43. http://dx.doi.org/10.1109/tce.2007.381698.

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Wang, Zhen, and Ye Cai Guo. "Blind Equalization Algorithm Based on the Orthogonal Wavelet Transform for SIMO Systems." Applied Mechanics and Materials 198-199 (September 2012): 1493–96. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.1493.

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In order to improve the equalization effects of the constant modulus blind equalization algorithm (CMA) for Single-Input and Multiple-Output (SIMO) systems, orthogonal wavelet transform constant modulus algorithm (WT-CMA) based on SIMO is proposed. This proposed algorithm uses the orthogonal wavelet transform to decrease the autocorrelation of the input signals to accelerate the convergence rate and reduce the steady-state error. Theoretical analysis and computer simulations shows that the proposed algorithm has better performance and smaller steady-state error in SIMO systems, it is very easy to achieve in engineering.
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Dissertations / Theses on the topic "SIMO systems"

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Karakutuk, Serkan. "Blind And Semi-blind Channel Order Estimation In Simo Systems." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12611107/index.pdf.

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Channel order estimation is an important problem in many fields including signal processing, communications, acoustics, and more. In this thesis, blind channel order estimation problem is considered for single-input, multi-output (SIMO) FIR systems. The problem is to estimate the effective channel order for the SIMO system given only the output samples corrupted by noise. Two new methods for channel order estimation are presented. These methods have several useful features compared to the currently known techniques. They are guaranteed to find the true channel order for noise free case and they perform significantly better for noisy observations. These algorithms show a consistent performance when the number of observations, channels and channel order are changed. The proposed algorithms are integrated with the least squares smoothing (LSS) algorithm for blind identification of the channel coefficients. LSS algorithm is selected since it is a deterministic algorithm and has some additional features suitable for order estimation. The proposed algorithms are compared with a variety of dierent algorithms including linear prediction (LP) based methods. LP approaches are known to be robust to channel order overestimation. In this thesis, it is shown that significant gain can be obtained compared to LP based approaches when the proposed techniques are used. The proposed algorithms are also compared with the oversampled single-input, single-output (SISO) system with a generic decision feedback equalizer, and better mean-square error performance is observed for the blind setting. Channel order estimation problem is also investigated for semi-blind systems where a pilot signal is used which is known at the receiver. In this case, two new methods are proposed which exploit the pilot signal in dierent ways. When both unknown and pilot symbols are used, a better estimation performance can be achieved compared to the proposed blind methods. The semi-blind approach is especially effective in terms of bit error rate (BER) evaluation thanks to the use of pilot symbols in better estimation of channel coecients. This approach is also more robust to ill-conditioned channels. The constraints for these approaches, such as synchronization, and the decrease in throughput still make the blind approaches a good alternative for channel order estimation. True and effective channel order estimation topics are discussed in detail and several simulations are done in order to show the significant performance gain achieved by the proposed methods.
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Ngo, Hien Quoc, Michail Matthaiou, Trung Q. Duong, and Erik G. Larsson. "Uplink Performance Analysis of Multicell MU-SIMO Systems with ZF Receivers." Linköpings universitet, Kommunikationssystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-92849.

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We consider the uplink of a multicell multiuser single-input multiple-output system where the channel experiences both small and large-scale fading. The data detection is done by using the linear zero-forcing technique, assuming the base station (BS) has perfect channel state information of all users in its cell. We derive  new, exact analytical expressions for the uplink rate, symbol error rate, and outage probability per user, as well as alower bound on the achievable rate. This bound is very tight and becomes exact in the large-number-of-antennas limit. We further study the asymptotic system performance in the regimes of high signal-to-noise ratio (SNR), large number of antennas, and large number of users per cell. We show that at high SNRs, the system is interference-limited and hence, we cannot improve the system performance by increasing the transmit power of each user. Instead, by increasing the number of BS antennas, the effects of interference and noise can be reduced, thereby improving the system performance. We demonstrate that, with very large antenna arrays at the BS, the transmit power of each user can be made inversely proportional to the number of BS antennas while maintaining a desired quality-of-service. Numerical results are presented to verify our analysis.
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Gao, Bo 1981. "Computationally efficient approaches for blind adaptive beamforming in SIMO-OFDM systems." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=115994.

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In single-input multiple-output (SIMO) systems based on orthogonal frequency division multiplexing (OFDM), adaptive beamforming at the receiver side can be used to combat the effect of directional co-channel interference (CCI). Since pilot-aided beamforming suffers from consuming precious channel bandwidth, there has been much interest in blind beamforming approaches that can adapt their weights by restoring certain properties of the transmitted signals. Within this class of blind algorithms, the recursive least squares constant modulus algorithm (RLS-CMA) is of particular interest due to its good overall CCI cancelation performance and fast convergence. Nevertheless, the direct use of RSL-CMA within a SIMO-OFDM receiver induces considerable computational complexity, since a distinct copy of the RLS-CMA must be run on each individual sub-carriers. In this thesis, we present two approaches to reduce the computational complexity of SIMO-OFDM beamforming based on the RLS-CMA, namely: frequency interpolation and distributed processing. The former approach, which exploits the coherence bandwidth of the broadband wireless channels, divides the sub-carriers into several contiguous groups and applies the RLS-CMA to a selected sub-carrier in each group. The weight vectors at other frequencies are then obtained by interpolation. The distributed processing approach relies on the partitioning of the receiving array into sub-arrays and the use of a special approximation in the RLS-CMA. This allows a partial decoupling of the algorithm which can then be run on multiple processors with reduced overall complexity. This approach is well-suited to collaborative beamforming i~ multi-node distributed relaying. Through numerical simulation experiments of a SIMO-OFDM system, it is demonstrated that the proposed modifications to the RLS-CMA scheme can lead to substantial computational savings with minimal losses in adaptive cancelation performance.
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Hu, Mathieu. "Cross-relation based blind identification of acoustic SIMO systems and applications." Thesis, Imperial College London, 2017. http://hdl.handle.net/10044/1/52430.

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Speech signals captured by microphones placed at a distance from the speaker are cor- rupted by reverberation, i.e. sound waves reflected off hard surfaces such as walls and objects. The spectral distortion caused by reverberation drastically decreases the perfor- mance of automatic speech recognition systems and may degrade the intelligibility and the quality of speech for human listeners. The increased use of devices controlled by distant speech therefore induces the need for dereverberation. A possible approach to dereverberation is that of system equalization, which consists of the blind estimation of the room impulse responses from noisy reverberant signals followed by an inversion of these impulse responses. This thesis investigates the first part of this two-stage approach. The cross-relation method is adopted and exploited in two different ways. The first way follows the adaptive filter framework, which was first introduced in the context of blind identification of room impulses responses in the Multi-Channel Least Mean Square. By considering a block update of this stochastic gradient algorithm, a noise robust algorithm is developed. The convergence rate of the resulting algorithm is then increased by using a locally optimal adaptive step-size. The cross-relation, expressed in the frequency domain, is then shown to contain the transfer function relating any of the microphone to a reference microphone. This relative transfer function can be used to reduce the number of variables to be estimated. However, the performance of the previous methods severely degrades when realisti- cally long room impulse responses are considered. An alternative interpretation of the cross-relation, from an annihilation filter perspective, is therefore explored. The resulting algorithm is shown to be able to estimate room impulse responses of thousands of taps. From a more practical perspective, the use of room impulses estimated at a poor accuracy is investigated for the problem of speaker diarization. The spatial information captured in the direct-to-reverberant ratio is shown to be robust to high levels of errors in the estimated room impulse responses. Blindly estimated direct-to-reverberant ratios combined with speech features in a single-channel diarization system are shown to provide additional information, which improves the performance of the diarization system.
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Bahri, Nesrine. "Une commande neuronale adaptative basée sur des émulateurs neuronal et multimodèle pour les systèmes non linéaires MIMO et SIMO." Thesis, Le Havre, 2015. http://www.theses.fr/2015LEHA0024/document.

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La porosité d'une plaque composite carbone / époxy de type RTM est connue par tomographie X. Une méthode de détermination de cette porosité par mesure de l'atténuation des ondes longitudinales à travers l'épaisseur de cette plaque est proposée. Ces mesures sont effectuées sur des surfaces de dimensions variables (quelques cm2 à quelques mm2) et permettent l’obtention de cartographies. Une correspondance porosité (tomo X) – atténuation (onde US) est déduite et analysée en fonction de la structure du matériau composite. Dans chaque cas, on estime la qualité des relations obtenues et on en déduit les limites de validité de la correspondance porosité-atténuation. Des premiers résultats de tomographie acoustiques sont obtenus<br>The porosity of a composite plate in carbon / epoxy of type RTM is known by used of tomography X. A method of determination of this porosity by measure of the mitigation of the longitudinal waves through the thickness of this kind of plate is proposed. These measures are made on surfaces of different sizes (from some cm2 to some mm2) and allow the obtaining of cartographies. A correspondence porosity (tomo X) - Mitigation (US wave) is deducted and analyzed according to the structure of the composite material. In every case, we estimate the quality of the obtained relations and we deduct the limits of validity of the correspondence between porosity and mitigation. First results of acoustic tomography are obtained
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Costa, Michele Nazareth da 1984. "Um estudo sobre as condições de inversão perfeita e de equalização não-supervisionada de canais SISO, SIMO e MIMO." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/259287.

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Orientador: João Marcos Travassos Romano, Ricardo Suyama<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação<br>Made available in DSpace on 2018-08-14T00:41:40Z (GMT). No. of bitstreams: 1 Costa_MicheleNazarethda_M.pdf: 1765125 bytes, checksum: ca7881285ef04b9d9226595f3dd1e90c (MD5) Previous issue date: 2009<br>Resumo: Esta dissertação teve como motivação inicial a busca de uma abordagem unificada para o problema de equalização não-supervisionada, a ser aplicada às configurações SISO, SIMO e MIMO. Tal abordagem se refere a dois aspectos fundamentais do problema: a estrutura do equalizador e a otimização de seus parâmetros. Desta forma, propomos uma mesma metodologia para estudar, nas três configurações citadas, o que denominamos de limitação estrutural e de limitação de critério. A primeira é caracterizada pela impossibilidade de inversão perfeita do canal fazendo uso de apenas filtros com resposta impulsiva finita (FIR); a segunda se refere às limitações quanto ao uso de estatísticas de ordem dois (EO2) para a obtenção do equalizador ótimo no caso não-supervisionado. Para tal análise, reunimos resultados um tanto dispersos na literatura para formalizar de maneira unificada e acessível os conceitos de sistema inversível e de sistema de fase mínima para as três configurações. Em seguida, empregamos o conceito de filtro de erro de predição linear para estudar o uso de EO2 em equalização, estendendo esse conceito também às três configurações<br>Abstract: This dissertation was motivated by the idea of developing a unified approach to the problem of unsupervised equalization, in the context of SISO, SIMO and MIMO channels. This approach is concerned with two fundamental aspects of the equalization problem: the structure of the equalizer and the optimization of its parameters. In this sense, we propose a same methodology to study, in the three aforementioned scenarios, two different limitations. The first one, which we denote structural limitation, is related to the impossibility of inverting any channel employing only finite impulse response (FIR) filters. The second one, which we call criterion limitation, refers to the limitation regarding the use of second order statistics (SOS) to obtain the equalizer in an unsupervised manner. In order to perform this analysis, we collected results that are rather scattered in the literature to formalize the concepts of invertible and minimum-phase systems in all three scenarios. Then, we use the concept of a prediction-error filter to study the limitation of SOS in the equalization problem<br>Mestrado<br>Telecomunicações e Telemática<br>Mestre em Engenharia Elétrica
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Krishnan, Narayanan. "Analysis of energy efficiency of cooperative MIMO schemes." Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1427.

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Chan, Kwong Hang Kevin. "An Analysis of Wireless High-speed Data Services for Cellular CDMA Systems." Thesis, University of Waterloo, 2002. http://hdl.handle.net/10012/860.

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The interest in the development of wireless high-speed data services is in response to the strong market demand for high-speed wireless Internet access. Current standards aim at delivering a peak data rate greater than 2Mbps on the forward link. Since data services and voice services are fundamentally different, new concepts were introduced in the design of the forward data channel. In addition, methods of evaluating the performance of a cellular CDMA system have to be revisited. This thesis proposes a method which can be used to find the forward link peak and average data rates, throughput and coverage of a cellular CDMA system which is capable of delivering high-speed wireless data. A summary of changes in design philosophy and recent advances in technologies which enable high-speed wireless data delivery are presented. The proposed method takes into account major aspects commonly found in the forward data channel and applies the generalized Shannon capacity formula for multi-element antenna (MEA) systems. The analysis focuses on the physical layer and is flexible enough to be adapted to various propagation environments, antenna configurations, multicode allocations, user distributions and cell site configurations. Sample numerical results for various multicode allocations are shown using a system model with two-tier interfering cells with one transmit antenna and two receive antennas operating under a frequency selective slow fading channel with propagation environment described by the Recommendation ITU-R M. 1225 indoor office, outdoor to indoor and pedestrian and vehicular test environments. Different transmit / receive antenna configurations and multicode allocations and their impact on the average data rate is also explored.
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Rabaça, Ricardo Seriacopi. "Estudo sobre os métodos de diversidade para sistemas de TV digital." Universidade Presbiteriana Mackenzie, 2017. http://tede.mackenzie.br/jspui/handle/tede/3479.

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Submitted by Marta Toyoda (1144061@mackenzie.br) on 2018-02-06T23:04:35Z No. of bitstreams: 2 RICARDO SERIACOPI RABAÇA.pdf: 12578451 bytes, checksum: 9aa6f50946d5c917a7ea4e5b6841ef6f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Approved for entry into archive by Paola Damato (repositorio@mackenzie.br) on 2018-04-03T12:57:50Z (GMT) No. of bitstreams: 2 RICARDO SERIACOPI RABAÇA.pdf: 12578451 bytes, checksum: 9aa6f50946d5c917a7ea4e5b6841ef6f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5)<br>Made available in DSpace on 2018-04-03T12:57:50Z (GMT). No. of bitstreams: 2 RICARDO SERIACOPI RABAÇA.pdf: 12578451 bytes, checksum: 9aa6f50946d5c917a7ea4e5b6841ef6f (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2017-08-08<br>Coordenação de Aperfeiçoamento de Pessoal de Nível Superior<br>Fundo Mackenzie de Pesquisa<br>This project presents the history, basic information and advantages of using Software De ned Radio (SDR), diversity, layer division multiplexing (LDM) technique and the latest digital TV standards in a digital communication system. These subjects have been relevant in the scienti c community, making the project attractive in terms of the possibility of discoveries and optimizations. After that, the implementation of a digital communication system using these technologies is proposed. This implementation was performed by means of GRC simulation software and the use of C++ and Python programming languages. Therefore, it was necessary to test the steps of coding, modulation and digital transmission / reception. Finally, tests were performed with systems that use diversity, for example, Single-Input Single-Output (SISO), as well as setting Single-Input Multiple-Output (SIMO), using the settings 1x 2, 1x3 and 1x4, in order to compare possible advantages in spectrum utilization, data rate and system robustness to interference.<br>O presente projeto apresenta o histórico, as informações básicas e as vantagens da utilização do rádio definido por software, do inglês Software Defined Radio (SDR), da diversidade, da técnica de multiplexacão por divisão em camadas, do inglês Layered Division Multiplexing (LDM) e dos mais modernos padrões de TV digital em um sistema de comunicação digital. Estes temas vêm repercutindo de forma relevante na comunidade científica, tornando o projeto atrativo em termos de possibilidade de descobertas e otimização. Posteriormente, a implementação de um sistema de comunicação digital unindo estas tecnologias _e proposta. Esta implementação foi realizada por meio do software de simulação GNU Radio Companion (GRC) e do uso das linguagens de programação C++ e Python. Para tanto, foi necessário testar as etapas de codificação, modulação e a transmissão/recepção digital. Finalmente, foram realizados testes com sistemas que utilizam diversidade, como, por exemplo, os métodos com uma entrada e uma saída, do inglês Single-Input Single-Output (SISO), além do método com uma entrada e múltiplas saídas, do inglês Single-Input Multiple-Output (SIMO), com as configurações 1x2, 1x3 e 1x4, com o intuito de comparar possíveis vantagens no aproveitamento do espectro, na taxa de dados e na robustez do sistema à interferências.
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Shankar, H. N. "Adaptive Control Of A General Class Of Finite Dimensional Stable LTI Systems." Thesis, Indian Institute of Science, 2000. https://etd.iisc.ac.in/handle/2005/225.

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We consider the problem of Adaptive Control of finite-dimensional, stable, Linear Time Invariant (LTI) plants. Amongst such plants, the subclass regarding which an upper bound on the order is not known or which are known to be nonminimum phase (zeros in the unstable region) pose formidable problems in their own right. On one hand, if an upper bound on the order of the plant is not known, adaptive control usually involves some form of order estimation. On the other hand, when the plant is allowed to be either minimum phase or nonminimum phase, the adaptive control problem, as is well-known, becomes considerably-less tractable. In this study, the class of unknown plants considered is such that no information is available on the upper bound of the plant order and, further, the plant may be either minimum phase or nonminimum phase. Albeit known to be stable, such plants throw myriads of challenges in the context of adaptive control. Adaptive control involving such plants has been addressed [79] in a Model Reference Adaptive Control (MRAC) framework. There, the inputs and outputs of the unknown plant are the only quantities available by measurement in terms of which any form of modeling of the unknown plant may be made. Inputs to the reference model have been taken from certain restricted classes of bounded signals. In particular, the three classes of inputs considered are piecewise continuous bounded functions which asymptotically approach • a nonzero constant, • a sinusoid, and • a sinusoid with a nonzero shift. Moreover, the control law is such that adaptation is carried out at specific instants separated by progressively larger intervals of time. The schemes there have been proved to be e-optimal in the sense of a suitably formulated optimality criterion. If, however, the reference model inputs be extended to the class of piecewise continuous bounded functions, that would compound the complexity of the adaptive control problem. Only one attempt [78] in adaptive control in such a setting has come to our notice. The problem there has been tackled by an application of the theory of Pade Approximations to time moments of an LTI system. Based on a time moments estimation procedure, a simple adaptive scheme for Single-Input Single-Output (SISO) systems with only a cascade compensator has been reported. The first chapter is essentially meant to ensure that the problem we seek to address in the field of adaptive control indeed has scope for research. Having defined Adaptive Control, we selectively scan through the literature on LTI systems, with focus on MRAC. We look out in particular for studies involving plants of which not much is known regarding their order and systems which are possibly nonminimum phase. We found no evidence to assert that the problem of adaptive control of stable LTI systems, not necessarily minimum phase and of unknown upper bound on the order, was explored enough, save two attempts involving SISO systems. Taking absence of evidence (of in-depth study) for evidence of absence, we make a case for the problem and formally state it. We preview the thesis. We set two targets before us in Chapter 2. The first is to review one of the existing procedures attacking the problem we intend to address. Since the approach is based on the notion of time moments of an LTI system, and as we are to employ Pade Approximations as a tool, we uncover these concepts to the limited extent of our requirement. The adaptive procedure, Plant Command Modifier Scheme (PCMS) [78], for SISO plants is reported in some detail. It stands supported on an algorithm specially designed to estimate the time moments of an LTI system given no more than its input and output. Model following there has been sought to be achieved by matching the first few time moments of the reference model by the corresponding ones of the overall compensated plant. The plant time moment estimates have been taken to represent the unknown plant. The second of the goals is to analyze PCMS critically so that it may serve as a forerunner to our work. We conclude the chapter after accomplishing these goals. In Chapter 3, we devise a time moment estimator for SISO systems from a perspective which is conceptually equivalent to, yet functionally different from, that appropriated in [78]. It is a recipe to obtain estimates of time moments of a system by computing time moment estimates of system input and output signals measured up to current time. Pade approximations come by handy for this purpose. The lacunae exposed by a critical examination of PCMS in Chapter 2 guide us to progressively refine the estimator. Infirmities in the control part of PCMS too have come to light on our probing into it. A few of these will be fixed by way of fabricating two exclusively cascade compensators. We encounter some more issues, traceable to the estimator, which need redressal. Instead of directly fine-tuning the estimator itself, as is the norm, we propose the idea of 'estimating' the lopsidedness of the estimator by using it on the fully known reference model. This will enable us to effect corrections and obtain admissible estimates. Next, we explore the possibility of incorporating feedback compensation in addition to the existing cascade compensation. With output error minimization in mind, we come up with three schemes in this category. In the process, we anticipate the risk of instability due to feedback and handle it by means of an instability preventer with an inbuilt instability detector. Extensive simulations with minimum and rionminimum phase unknown plants employing the various schemes proposed are presented. A systematic study of simulation results reveals a dyad of hierarchies of progressively enhanced overall performance. One is in the sequence of the proposed schemes and the other in going for matching more and more moments. Based on our experiments we pick one of the feedback schemes as the best. Chapter 4 is conceived of as a bridge between SISO and multivariable systems. A transition from SISO to Multi-Input Multi-Output (MIMO) adaptive control is not a proposition confined to the mathematics of dimension-enhancement. A descent from the MIMO to the SISO case is expected to be relatively simple, though. So to transit as smoothly and gracefully as possible, some issues have to be placed in perspective before exploring multivariable systems. We succinctly debate on the efforts in pursuit of the exact vis-a-vis the accurate, and their implications. We then set some notations and formulate certain results which serve to unify and simplify the development in the subsequent three chapters. We list a few standard results from matrix theory which are to be of frequent use in handling multivariable systems. We derive control laws for Single-Input Multi-Output (SIMO) systems in Chapter 5. Expectedly, SIMO systems display traits of observability and uncontrollability. Results of illustrative simulations are furnished. In Chapter 6, we formulate control laws for Multi-Input Single-Output (MISO) systems. Characteristics of unobservability and controllability stand out there. We present case studies. Before actually setting foot onto MIMO systems, we venture to conjecture on what to expect there. We work out all the cascade and feedback adaptive schemes for square and nonsquare MIMO systems in Chapter 7. We show that MIMO laws when projected to MISO, SIMO and SISO cases agree with the corresponding laws in the respective cases. Thus the generality of our treatment of MIMO systems over other multivariable and scalar systems is established. We report simulations of instances depicting satisfactory performance and highlight the limitations of the schemes in tackling the family of plants of unknown upper bound on the order and possibly nonminimum phase. This forms the culmination of our exercise which took off from the reported work involving SISO systems [78]. Up to the end of the 7th chapter, we are in pursuit of solutions for the problem as general as in §1.4. For SISO systems, with input restrictions, the problem has been addressed in [79]. The laws proposed there carry out adaptation only at certain discrete instants; with respect to a suitably chosen cost, the final laws are proved to be e>optimal. In Chapter 8, aided by initial suboptimal control laws, we finally devise two algorithms with continuous-time adaptation and prove their optimality. Simulations with minimum and nonminimum phase plants reveal the effectiveness of the various laws, besides throwing light on the bootstrapping and auto-rectifying features of the algorithms. In the tail-piece, we summarize the work and wind up matters reserved for later deliberation. As we critically review the present work, we decant the take-home message. A short note on applications followed by some loud thinking as a spin-off of this report will take us to finis.
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Books on the topic "SIMO systems"

1

Matisoff, James A. Sino-Tibetan numeral systems: Prefixes, protoforms and problems. Pacific Linguistics, Research School of Pacific and Asian Studies, Australian National University, 1997.

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United States. Environmental Protection Agency. Control Technology Center., ed. Background document for the surface impoundment modeling system (SIMS): Version 2.0. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Control Technology Center, 1989.

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Watkins, Sheryl L. Background document for the surface impoundment modeling system (SIMS): Version 2.0. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Control Technology Center, 1990.

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United States. Environmental Protection Agency. Control Technology Center., ed. Background document for the surface impoundment modeling system (SIMS): Version 2.0. U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Control Technology Center, 1989.

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Tomboulian, Sherryl. A system for routing arbitrary directed graphs on SIMD architectures. ICASE, 1987.

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United States. Army Aviation Research and Technology Activity. Propulsion Directorate. and United States. National Aeronautics and Space Administration., eds. An expert system to perform on-line controller tuning. National Aeronautics and Space Administration, 1990.

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Edward, Barkmeyer, and Christopher Neil, eds. Background study: Requisite elements, rationale, and technology overview for the Systems Integration for Manufacturing Applications (SIMA) Program. U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1995.

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Gupta, Prasanta Sen. China's belief system and Sino-Indian relations: The Maoist era. Minerva Associates (Publications), 1998.

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Mihaela, Gavrila, ed. Il mondo che siamo: Per una sociologia dei media e dei linguaggi digitali. Liguori, 2008.

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Juang, Jer-Nan. Predictive feedback and feedforward control for systems with unknown disturbances. National Aeronautics and Space Administration, Langley Research Center, 1998.

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Book chapters on the topic "SIMO systems"

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Yu, Chengpu, Lihua Xie, Michel Verhaegen, and Jie Chen. "Blind Identification of SIMO FIR Systems." In Blind Identification of Structured Dynamic Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7574-4_5.

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Ganotra, Sanjog. "Power Distribution Control for SIMO Wireless Power Transfer Systems." In Proceedings of Second International Conference on Computing, Communications, and Cyber-Security. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0733-2_6.

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Prasad, Ramjee, Suvra Sekhar Das, and Muhammad Imadur Rahman. "Joint Link Adaptation and Resource Allocation in SISO/SIMO Systems." In Adaptive PHY-MAC Design for Broadband Wireless Systems. River Publishers, 2022. http://dx.doi.org/10.1201/9781003336969-10.

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Jing, Xingjian. "Case Studies: Controller Design of Vehicle Suspension Systems—A SIMO Nonlinear System Approach." In The Bio-Inspired X-Structure/Mechanism Approach for Exploring Nonlinear Benefits in Engineering. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-5769-8_8.

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Kumar, Guntha Sai, R. Dahlia Devapriya, and P. Sudharsan. "Analysis of SIMO Wireless Communication Systems Using Intelligent Reflecting Surfaces (IRS)." In Proceedings of the 2nd International Conference on Signal and Data Processing. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1410-4_7.

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Xu, Weiyang, Huiqiang Xie, and Shengbo Xu. "Performance Analysis of Non-coherent Massive SIMO Systems with Antenna Correlation." In Communications and Networking. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06161-6_44.

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Hlaing, Ngu War, Ali Farzamnia, Manas Kumar Haldar, and Tohid Yousefi Rezaii. "BER Analysis of SIMO and MIMO Systems with Rayleigh Fading Using SIMULINK." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2406-3_59.

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Mahamadu, Mahamuda Alhaji, and Zheng Ma. "Performance of Linearly Modulated SIMO High Mobility Systems with Channel Estimation Errors." In Communications and Networking. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-06161-6_9.

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Rajarajeshwari, K. C., T. Poornima, K. R. Gokul Anand, and S. V. Kumari. "SIMO Array Characterized THz Antenna Resonating at Multiband Ultra High Frequency Range for 6G Wireless Applications." In Terahertz Devices, Circuits and Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4105-4_7.

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Tran-Ha, Vu, Duc-Dung Tran, Dac-Binh Ha, and Een-Kee Hong. "On the Performance of MU SIMO/MIMO UWB Communication Systems Applying Time-Reversal Technique." In Transactions on Engineering Technologies. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9115-1_34.

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Conference papers on the topic "SIMO systems"

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Wei Bai, Haifen Yang, and Zhiyong Bu. "Blind channel identification in SIMO-OFDM systems." In 2004 International Conference on Communications, Circuits and Systems. IEEE, 2004. http://dx.doi.org/10.1109/icccas.2004.1346078.

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Manolakos, Alexandras, Mainak Chowdhury, and Andrea J. Goldsmith. "Constellation design in noncoherent massive SIMO systems." In GLOBECOM 2014 - 2014 IEEE Global Communications Conference. IEEE, 2014. http://dx.doi.org/10.1109/glocom.2014.7037381.

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Lawal, Abdulmajid, Karim Abed-Meraim, Qadri Mayyala, Navid Iqbal, and Azzedine Zerguine. "Blind MMSE Equalizer for Nonlinear SIMO Systems." In 2021 18th International Multi-Conference on Systems, Signals & Devices (SSD). IEEE, 2021. http://dx.doi.org/10.1109/ssd52085.2021.9429382.

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Omatu, S., T. Fujinaka, Y. Kishida, and M. Yoshioka. "Self-tuning neuro-PID for SIMO systems." In 1999 European Control Conference (ECC). IEEE, 1999. http://dx.doi.org/10.23919/ecc.1999.7100014.

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Nath, Nabajyoti, and Sanya Anees. "Performance Analysis of SIMO-UWOC System." In 2020 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS). IEEE, 2020. http://dx.doi.org/10.1109/ants50601.2020.9342794.

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Zhang, Xiaofei, and Dazhuan Xu. "PARAFAC Multiuser Detection for SIMO-CDMA System." In 2006 International Conference on Communications, Circuits and Systems. IEEE, 2006. http://dx.doi.org/10.1109/icccas.2006.284761.

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Chowdhury, Mainak, Alexandros Manolakos, Felipe Gomez-Cuba, Elza Erkip, and Andrea J. Goldsmith. "Capacity scaling in noncoherent wideband massive SIMO systems." In 2015 IEEE Information Theory Workshop (ITW). IEEE, 2015. http://dx.doi.org/10.1109/itw.2015.7133138.

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Mao, Tianqi, and Zhaocheng Wang. "Physical-Layer Security Enhancement for SIMO-MBM Systems." In GLOBECOM 2018 - 2018 IEEE Global Communications Conference. IEEE, 2018. http://dx.doi.org/10.1109/glocom.2018.8647748.

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Alayyan, Faisal O., Raed M. Shubair, Yee Hong Leung, Abdelhak M. Zoubir, and Omar Alketbi. "Blind channel identification for OFDM-based SIMO systems." In 2008 International Conference on Innovations in Information Technology (IIT). IEEE, 2008. http://dx.doi.org/10.1109/innovations.2008.4781633.

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Bai, Shaozhuang, Zhenzhen Gao, and Xuewen Liao. "Diversity-Achieving Secure Scheme for SIMO-MBM Systems." In 2019 IEEE/CIC International Conference on Communications in China (ICCC). IEEE, 2019. http://dx.doi.org/10.1109/iccchina.2019.8855890.

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Reports on the topic "SIMO systems"

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Fujita, Mel. Smart Integrated Microsensor System (SIMS). Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada259430.

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Bell, B. SIMS: The SLAC Industrial Measurement System. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/878879.

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Garcia-Sanz, Mario, and Carlos Molins. Advanced Quantitative Robust Control Engineering: New Solutions for Automatic Loop-Shaping for SISO and MIMO Systems. Part 1: SISO Systems. Defense Technical Information Center, 2009. http://dx.doi.org/10.21236/ada521387.

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Fields, C. Sequencing Information Management System (SIMS). Final report. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/207362.

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Harpring, L. J. SIMON Host Computer System requirements and recommendations. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/5654697.

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Harpring, L. J. SIMON Host Computer System requirements and recommendations. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/10130242.

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Swinford, Richard. An AFM-SIMS Nano Tomography Acquisition System. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.5369.

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Bialasiewicz, J. T., E. Muljadi, G. R. Nix, and S. Drouilhet. RPM-SIM (Renewable Energy Power System Modular Simulator) user's guide. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/753768.

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Abassy, Malgorzata, and Weronika Krupa. Sino-Russo-Iranian Tech Cooperation as Threat for the EU: Systemic Approach. EuroHub4Sino, 2025. https://doi.org/10.31175/eh4s.3c7e.

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Abstract:
The strategic convergence between Russia, Iran, and China poses a growing systemic threat to the European Union. Despite differing regional agendas, these three powers are increasingly aligned in key areas such as cybersecurity, military technology transfers, intelligence cooperation, and disinformation campaigns. Their coordinated efforts undermine the EU’s critical infrastructure, weaken its strategic autonomy, and erode trust in democratic institutions by targeting sectors such as energy, finance, healthcare, and electoral integrity. Although the EU has implemented sanctions and reinforced its cybersecurity framework, it continues to address these actors largely in isolation, failing to recognize the cumulative security impact of their trilateral cooperation. Particular vulnerabilities include the transfer of advanced knowledge and dual-use technologies via academic and industrial partnerships with China, the use of hybrid warfare tactics by Iran—including cyberattacks and propaganda—and Russia’s ongoing infiltration of European digital networks and information ecosystems. To address this, the EU must adopt a coherent, forward-looking strategythat moves beyond fragmented responses. This entails the establishment of a centralized threat assessment hub coordinating intelligence from Member States, the restriction of academic and technological partnerships with high-risk third countries, the reinforcement of cyber resilience through joint infrastructure protection drills with NATO, and the creation of a targeted investment mechanism to reduce dependency on foreign critical technologies. These concrete instruments, when integrated, can strengthen Europe’s defense capabilities, reduce strategic dependencies, and safeguard its democratic and technological sovereignty.
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Bialasiewicz, J. T., E. Muljadi, G. R. Nix, and S. Drouilhet. Renewable Energy Power System Modular SIMulators: RPM-Sim User's Guide (Supersedes October 1999 edition). Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/777317.

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