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Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols i...
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Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: 1) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; 2) longitudinal studies, where temporal structural or anatomical changes are investigated; and 3) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner.
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Airborne wind turbines (AWTs) represent a radically new and fascinating concept for future harnessing of wind power. This concept consists of realizing only the blades of a conventional wind turbine (CWT) in the form of a power ki...
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Airborne wind turbines (AWTs) represent a radically new and fascinating concept for future harnessing of wind power. This concept consists of realizing only the blades of a conventional wind turbine (CWT) in the form of a power kite flying at high speed perpendicular to the wind. On the kite are mounted a turbine, an electrical generator, and a power electronics converter. The electric power generated is transmitted via a medium voltage cable to the ground. Because of the high flight speed of the power kite, several times the actual wind speed, only a very small swept area of the turbine is required according to Betz's Law and/or a turbine of low weight for the generation of a given electric power. Moreover, because of the high turbine rotational speed, no gear transmission is necessary and the size of the generator is also reduced. For takeoff and landing of the power kite, the turbines act as propellers and the generators as motors, i.e., electric power is supplied so that the system can be maneuvered like a helicopter. In the present work, the configuration of power electronics converters for the implementation of a 100 kW AWT is considered. The major aspect here is the trade-off between power-to-weight ratio (W/kg) and efficiency. The dependence of cable weight and cable losses on the voltage level of power transmission is investigated, and a comparison is made between low voltage (LV) and medium voltage (MV) versions of generators. Furthermore, the interdependence of the weight and efficiency of a bidirectional dual active bridge dc–dc converter for coupling the rectified output voltage of a LV generator to the MV cable is discussed. On the basis of this discussion, the concept offering the best possible compromise of weight and efficiency in the power electronics system is selected and a model of the control behavior is derived for both the power flow directions. A control structure is then proposed and dimensioned. Furthermore, questions of electrom- gnetic compatibility and electrical safety are treated. In conclusion, the essential results of this paper are summarized, and an outlook on future research is given. To enable the reader to make simplified calculations and a comparison of a CWT with an AWT, the aerodynamic fundamentals of both the systems are summarized in highly simplified form in an Appendix, and numerical values are given for the 100 kW system discussed in this paper.
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The binary deletion channel is the simplest point-to-point communication channel that models lack of synchronization. Input bits are deleted independently with probability $d$, and when they are not deleted, they are not affected...
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The binary deletion channel is the simplest point-to-point communication channel that models lack of synchronization. Input bits are deleted independently with probability $d$, and when they are not deleted, they are not affected by the channel. Despite significant effort, little is known about the capacity of this channel and even less about optimal coding schemes. In this paper, we develop a new systematic approach to this problem, by demonstrating that capacity can be computed in a series expansion for small deletion probability. We compute three leading terms of this expansion, and find an input distribution that achieves capacity up to this order. This constitutes the first optimal random coding result for the deletion channel. The key idea employed is the following: We understand perfectly the deletion channel with deletion probability $d=0$. It has capacity 1 and the optimal input distribution is iid Bernoulli$(1/2)$. It is natural to expect that the channel with small deletion probabilities has a capacity that varies smoothly with $d$, and that the optimal input distribution is obtained by smoothly perturbing the iid Bernoulli$(1/2)$ process. Our results show that this is indeed the case.
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Noise is associated with all the components of the oscillator circuit; however, the major contribution of the noise in an oscillator is from the active device, which introduces amplitude modulation (AM) and phase modulation (PM) n...
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Noise is associated with all the components of the oscillator circuit; however, the major contribution of the noise in an oscillator is from the active device, which introduces amplitude modulation (AM) and phase modulation (PM) noise [1]-[103]. The conventional wisdom is to ignore AM component of the noise because the gain limiting effects of the active device operating under saturation, allowing only little variation in the output amplitude due to the noise in comparison to PM noise component, which directly affects the frequency stability of the oscillator and creates noise sidebands. But in reality, many oscillator topologies create significant AM noise, therefore effective noise contribution is the combination of 1/f spectrum with the 1/f 2 effect in all PM, makes the low_frequency noise much greater, and that's where the information in most modulated signals resides [1]-[3].
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We propose joint spatial division and multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base s...
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We propose joint spatial division and multiplexing (JSDM), an approach to multiuser MIMO downlink that exploits the structure of the correlation of the channel vectors in order to allow for a large number of antennas at the base station while requiring reduced-dimensional channel state information at the transmitter (CSIT). JSDM achieves significant savings both in the downlink training and in the CSIT uplink feedback, thus making the use of large antenna arrays at the base station potentially suitable also for frequency division duplexing (FDD) systems, for which uplink/downlink channel reciprocity cannot be exploited. In the proposed scheme, the multiuser MIMO downlink precoder is obtained by concatenating a prebeamforming matrix, which depends only on the channel second-order statistics, with a classical multiuser precoder, based on the instantaneous knowledge of the resulting reduced dimensional “effective” channel matrix. We prove a simple condition under which JSDM incurs no loss of optimality with respect to the full CSIT case. For linear uniformly spaced arrays, we show that such condition is approached in the large number of antennas limit. For this case, we use Szego's asymptotic theory of Toeplitz matrices to show that a DFT-based prebeamforming matrix is near-optimal, requiring only coarse information about the users angles of arrival and angular spread. Finally, we extend these ideas to the case of a 2-D base station antenna array, with 3-D beamforming, including multiple beams in the elevation angle direction. We provide guidelines for the prebeamforming optimization and calculate the system spectral efficiency under proportional fairness and max-min fairness criteria, showing extremely attractive performance. Our numerical results are obtained via asymptotic random matrix theory, avoiding lengthy Monte Carlo simulations and providing accurate results for realistic (finite) number of antennas and users.
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Legacy networks, both fixed and mobile, which were originally designed for voice communications, are progressively migrating to new infrastructures that promise to revolutionize the services offered. In this paper, we will cover t...
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Legacy networks, both fixed and mobile, which were originally designed for voice communications, are progressively migrating to new infrastructures that promise to revolutionize the services offered. In this paper, we will cover this new generation of personal communication services, with an emphasis on the family of Internet protocol (IP)-based multimedia subsystem (IMS)-aided infrastructure that relies on the session initiation protocol (SIP). As a benefit, the end users will enjoy a new generation of personal communications services that are accessible anywhere and anytime. These services are directly related to the end users rather than to their diverse devices. It is anticipated that the new deployments of next-generation networks (all-IP based) will accelerate the adoption of the IMS technology.
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This paper introduces the novel concept of proactive resource allocation for wireless networks, through which the predictability of user behavior is exploited to balance the wireless traffic over time, and significantly reduces th...
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This paper introduces the novel concept of proactive resource allocation for wireless networks, through which the predictability of user behavior is exploited to balance the wireless traffic over time, and significantly reduces the bandwidth required to achieve a given blocking/outage probability. We start with a simple model in which smart wireless devices are assumed to predict the arrival of new requests and submit them to the network $T$ time slots in advance. Using tools from large deviation theory, we quantify the resulting prediction diversity gain to establish that the decay rate of the outage event probabilities increases with the prediction duration $T$. Remarkably, we also show that, in the cognitive networking scenario, the appropriate use of proactive resource allocation by primary users improves the diversity gain of the secondary network at no cost in the primary network diversity. We also shed light on multicasting with predictable demands and show that proactive multicast networks can achieve a significantly higher diversity gain that scales superlinearly with $T$. Finally, we conclude by a discussion of the new research questions posed under the umbrella of the proposed proactive wireless resource framework.
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A method for efficiently constructing polar codes is presented and analyzed. Although polar codes are explicitly defined, straightforward construction is intractable since the resulting polar bit-channels have an output alphabet t...
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A method for efficiently constructing polar codes is presented and analyzed. Although polar codes are explicitly defined, straightforward construction is intractable since the resulting polar bit-channels have an output alphabet that grows exponentially with the code length. Thus, the core problem that needs to be solved is that of faithfully approximating a bit-channel with an intractably large alphabet by another channel having a manageable alphabet size. We devise two approximation methods which “sandwich” the original bit-channel between a degraded and an upgraded version thereof. Both approximations can be efficiently computed and turn out to be extremely close in practice. We also provide theoretical analysis of our construction algorithms, proving that for any fixed $varepsilon > 0$ and all sufficiently large code lengths $n$, polar codes whose rate is within $varepsilon $ of channel capacity can be constructed in time and space that are both linear in $n$.
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In this paper, we propose low-complexity algorithms based on Monte Carlo sampling for signal detection and channel estimation on the uplink in large-scale multiuser multiple-input–multiple-output (MIMO) systems with tens to hundr...
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In this paper, we propose low-complexity algorithms based on Monte Carlo sampling for signal detection and channel estimation on the uplink in large-scale multiuser multiple-input–multiple-output (MIMO) systems with tens to hundreds of antennas at the base station (BS) and a similar number of uplink users. A BS receiver that employs a novel mixed sampling technique (which makes a probabilistic choice between Gibbs sampling and random uniform sampling in each coordinate update) for detection and a Gibbs-sampling-based method for channel estimation is proposed. The algorithm proposed for detection alleviates the stalling problem encountered at high signal-to-noise ratios (SNRs) in conventional Gibbs-sampling-based detection and achieves near-optimal performance in large systems with $M$-ary quadrature amplitude modulation ( $M$-QAM). A novel ingredient in the detection algorithm that is responsible for achieving near-optimal performance at low complexity is the joint use of a mixed Gibbs sampling (MGS) strategy coupled with a multiple restart (MR) strategy with an efficient restart criterion. Near-optimal detection performance is demonstrated for a large number of BS antennas and users (e.g., 64 and 128 BS antennas and users). The proposed Gibbs-sampling-based channel estimation algorithm refines an initial estimate of the channel obtained during the pilot phase through iterations with the proposed MGS-based detection during the data phase. In time-division duplex systems where channel reciprocity holds, these channel estimates can be used for multiuser MIMO precoding on the downlink. The proposed receiver is shown to achieve good performance and scale well for large dimensions.
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The $K$-user single-input single-output (SISO) additive white Gaussian noise (AWGN) interference channel and $2times K$ SISO AWGN X channel are considered, where the transmitters have delayed channel state information (CSI) throug...
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The $K$-user single-input single-output (SISO) additive white Gaussian noise (AWGN) interference channel and $2times K$ SISO AWGN X channel are considered, where the transmitters have delayed channel state information (CSI) through noiseless feedback links. Multiphase transmission schemes are proposed for both channels which possess novel ingredients, namely, multiphase partial interference nulling, distributed interference management via user scheduling, and distributed higher order symbol generation. The achieved degree-of-freedom (DoF) values are greater than the best previously known DoFs for both channels with delayed CSI at the transmitters.
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