@inproceedings{40804,
  abstract     = {{This paper advocates that the convergent systems property and incremental stability are two intimately related though different properties. Sufficient conditions for the convergent systems property usually rely upon first showing that a system is incrementally stable, as e.g. in the celebrated Demidovich condition. However, in the current paper it is shown that incremental stability itself does not imply the convergence property, or vice versa. Moreover, characterizations of both properties in terms of Lyapunov functions are given. Based on these characterizations, it is established that the convergence property implies incremental stability for systems evolving oncompact sets, and also when a suitable uniformity condition is satisfied.}},
  author       = {{Rüffer, Björn S. and van de Wouw, Nathan and Mueller, Markus}},
  booktitle    = {{Proc. 51st IEEE Conf. Decis. Control}},
  pages        = {{2958–2963}},
  title        = {{{From convergent dynamics to incremental stability}}},
  year         = {{2012}},
}

@inproceedings{40808,
  abstract     = {{The monogenic signal allows us to decompose a two-dimensional real signal into a local amplitude, a local orientation, and a local phase. In this paper, we introduce the random monogenic signal and study its second-order statistical properties. The monogenic signal may be represented as a quaternion-valued signal. We show that for homogeneous random fields, we need exactly two quaternion-valued covariance functions for a complete second-order description. We also introduce a stochastic model for unidirectional signals and a measure of unidirectionality.}},
  author       = {{Olhede, S. C. and Ramírez, D. and Schreier, P. J.}},
  booktitle    = {{Proc.\ IEEE Int.\ Conf.\ Image Process.}},
  title        = {{{The Random Monogenic Signal}}},
  doi          = {{10.1109/ICIP.2012.6467404}},
  year         = {{2012}},
}

@article{40805,
  abstract     = {{We study the instantaneous frequency (IF) of continuous-time, complex-valued, zero-mean, proper, mean-square differentiable, nonstationary Gaussian stochastic processes. We compute the probability density function for the IF for fixed time, which generalizes a result known for wide-sense stationary processes to nonstationary processes. For a fixed point in time, the IF has either zero or infinite variance. For harmonizable processes, we obtain as a consequence the result that the mean of the IF, for fixed time, is the normalized first-order frequency moment of the Wigner spectrum.}},
  author       = {{Wahlberg, Patrik and Schreier, Peter J.}},
  journal      = {{Probab.\ Math.\ Statist.}},
  pages        = {{69–92}},
  title        = {{{On the instantaneous frequency of Gaussian stochastic processes}}},
  volume       = {{32}},
  year         = {{2012}},
}

@article{40806,
  abstract     = {{This work reports on the implementation of different absorption micro-filters based on a dye-doped hybrid organic-inorganic xerogel polymeric material synthesized by the sol-gel process. Microstructures containing eight different filter widths were fabricated in polydimethylsiloxane (PDMS), bonded to glass substrates and filled with the corresponding dye doped polymeric material by a soft lithography approach. The filtering capacity as a function of dye concentration and filter width was studied and revealed a linear dependence with both parameters, as expected according to the Beer-Lambert law. Zero passband transmittance values and relatively sharp stopband regions were achieved with all the filters, also showing rejection levels between ?6 dB and ?55 dB. Finally, such filters were monolithically integrated into a disposable fluorescence-based photonic lab-on-a-chip (PhLoC) approach. Calibration curves carried out with a model fluorophore target analyte showed an over two-fold increase in sensitivity and a thirty-fold decrease of the limit of detection (LOD) compared with the values recorded using the same PhLoC system but without the polymeric filter structure. The results presented herein clearly indicate the feasibility of these xerogel-based absorbance filtering structures for being applied as low-cost optical components that can be easily incorporated into disposable fluorescence-based photonic lab on a chip systems}},
  author       = {{Carregal-Romero, Ester and Fernandez-Sanchez, Cesar and Eguizabal, Alma and Demming, Stefanie and Büttgenbach, Stephanus and Llobera, Andreu}},
  journal      = {{Opt. Express}},
  number       = {{21}},
  pages        = {{23700–23719}},
  title        = {{{Development and integration of xerogel polymeric absorbance micro-filters into lab-onchip systems}}},
  doi          = {{10.1364/OE.20.023700}},
  volume       = {{20}},
  year         = {{2012}},
}

@inproceedings{40809,
  abstract     = {{Interference alignment (IA) has been shown to achieve the maximum degrees of freedom in the multiple-input multiple-output (MIMO) K-user interference channel (IFC). In the presence of frequency-selective channels, orthogonal frequency-division multiplexing (OFDM) is typically used to deal with the multipath nature of the channel. While IA techniques can be applied in a per-subcarrier basis (post-FFT), the existence of symbol timing offsets (STOs) between the desired and the interfering OFDM symbols decreases the system performance dramatically. To solve this problem, we design pre-FFT precoders and decoders for single-beam MIMO IFCs for OFDM transmissions. Since the IA decoders operate before the FFT, they mitigate the interference before synchronization takes place. We show that our proposed scheme improves the system performance when STOs occur, in comparison with traditional post-FFT IA techniques. We provide simulation results to compare post- and pre-FFT beamforming techniques and to illustrate the performance of the proposed method.}},
  author       = {{Lameiro, Christian and Vía, Javier and Santamaría, Ignacio and Heath Jr., Robert W.}},
  booktitle    = {{Proc. Int. Symp. Wireless Comm. Syst.}},
  title        = {{{Pre- and Post-FFT Interference Leakage Minimization for MIMO OFDM Networks}}},
  doi          = {{10.1109/ISWCS.2012.6328429}},
  year         = {{2012}},
}

@inproceedings{40813,
  abstract     = {{In this paper, the problem of multiantenna spectrum sensing in cognitive radio (CR) is addressed within a Bayesian framework. Unlike previous works, our Bayesian model places priors directly on the spatial covariance matrices under both hypotheses, as well as on the probability of channel occupancy. Specifically, we use inverse-gamma and complex inverse-Wishart distributions as conjugate priors for the null and alternative hypotheses, respectively; and a Bernoulli distribution as the prior for channel occupancy. At each sensing period, Bayesian inference is applied and the posterior of channel occupancy is thresholded for detection. After a suitable approximation, the posteriors are employed as priors for the next sensing frame, which can be beneficial in slowly time-varying environments. By means of simulations, the proposed detector is shown to outperform the Generalized Likelihood Ratio Test (GLRT) detector.}},
  author       = {{Manco-Vásquez, J. and Lazaro-Gredilla, M. and Ramírez, D. and Vía, J. and Santamaría, I.}},
  booktitle    = {{Proc.\ IEEE Sensor Array and Multichannel Signal Process. Work.}},
  title        = {{{Bayesian Multiantenna Sensing for Cognitive Radio}}},
  doi          = {{10.1109/SAM.2012.6250566}},
  year         = {{2012}},
}

@inproceedings{40814,
  abstract     = {{In this paper we propose an efficient transmission strategy for the two-way relay channel (TWRC) with multiple relays, when these are multiple-input multiple-output (MIMO) transceivers that apply the amplify-and-forward (AF) protocol. Although the optimal beamforming strategy is known, it requires a central node, with channel state information (CSI) of the entire network, to compute all the beamforming matrices, which is impractical. To reduce the overhead, in this paper we present a distributed algorithm for the computation of the relay beamforming matrices. The proposed algorithm divides the problem in two stages. First, each relay computes its own beamforming matrix in parallel using only local CSI. Next, a distributed beamforming is applied to make the signals add up coherently at the nodes. Although the proposed algorithm is suboptimal, we show through simulations that it performs very close to the optimal achievable rate region.}},
  author       = {{Lameiro, Christian and Vía, Javier and Santamaría, Ignacio}},
  booktitle    = {{Proc.\ IEEE Sensor Array and Multichannel Signal Process. Work.}},
  title        = {{{A Distributed Algorithm for Two-Way Multiple-Relay Networks}}},
  doi          = {{10.1109/SAM.2012.6250440}},
  year         = {{2012}},
}

@inproceedings{40816,
  abstract     = {{Textural analysis of tissue scattering images is proposed for healthy versus tumor discrimination. Scattering center density varies from normal to tumor tissues and this variation is translated into different textures in the scattering power map. Adipose tissue shows low autocorrelation values while tumor tissues present higher entropies than normal tissue. Consequently, a combination of autocorrelation and entropy values allows ready tissue discrimination by a supervised linear classifier. The proposed approach has been validated over a set of 29 breast tissue samples achieving a sensitivity of 73.59% and specificity of 82.40%.}},
  author       = {{Eguizabal, Alma and Laughney, Ashley M. and Garcia-Allende, P. Beatriz and Krishnaswamy, Venkataramanan and Wells, Wendy A. and Paulsen, Keith D. and Pogue, Brian W. and Lopez-Higuera, Jose M. and Conde, Olga M.}},
  booktitle    = {{IEEE 9th International Symposium on Biomedical Imaging}},
  title        = {{{Textural analysis of optical scattering for identification of cancer in breast surgical specimens}}},
  year         = {{2012}},
}

@inproceedings{40815,
  abstract     = {{A surgeon-guided independent component analysis from optical reflectance measurements is proposed for breast tumor delineation. Independent Component Analysis is first applied to extract the most relevant features from local measures of broadband reflectance and then a tumor probability indicator is obtained and provided utilizing surgeon assistance to resolve the inherent ambiguities in the independent component calculation. A set of 29 breast tissue samples have been diagnosed achieving a sensitivity of 90.57%, and specificity of 93.98%.}},
  author       = {{Eguizabal, Alma and Laughney, Ashley M. and Garcia-Allende, P. Beatriz and Krishnaswamy, Venkataramanan and Wells, Wendy A. and Paulsen, Keith D. and Pogue, Brian W. and Lopez-Higuera, Jose M. and Conde, Olga M.}},
  booktitle    = {{IEEE 9th International Symposium on Biomedical Imaging}},
  title        = {{{ICA-guided delineation of breast cancer pathology}}},
  year         = {{2012}},
}

@inproceedings{40803,
  abstract     = {{This paper considers nonlinear dynamical networks consisting of individually iISS (integral input-to-statestable) subsystems which are not necessarily ISS (input-to-statestable). Stability criteria for internal and external stability of the networks are developed in view of both necessity and sufficiency. For the sufficiency, we show how we can construct a Lyapunov function of the network explicitly under the assumption that a cyclic small-gain condition is satisfied. The cyclic small-gain condition is shown to be equivalent to a matrix-like condition. The two conditions and their equivalence precisely generalize some central ISS results in the literature. Moreover, the necessity of the matrix-like condition is established. The allowable number of non-ISS subsystems for stability of the network is discussed through several necessity conditions.}},
  author       = {{Ito, Hiroshi and Jiang, Zhong-Ping and Dashkovskiy, Sergey N. and Rüffer, Björn S.}},
  booktitle    = {{Proc. 51st IEEE Conf. Decis. Control}},
  pages        = {{4158–4164}},
  title        = {{{A cyclic small-gain condition and an equivalent matrix-like criterion for iISS networks}}},
  year         = {{2012}},
}

@inproceedings{40802,
  abstract     = {{This invited paper is a significantly shortened excerpt of the article S. N. DASHKOVSKIY, B. S. RÜFFER, AND F. R. WIRTH, Small gain theorems for large scale systems and construction of ISS Lyapunov functions, SIAM J. Control Optim., 48 (2010), pp. 4089–4118. We consider interconnections of n nonlinear subsystems in the input-to-state stability (ISS) framework. Foreach subsystem an ISS Lyapunov function is given that treats the other subsystems as independent inputs. A gain matrix is used to encode the mutual dependencies of the systems in the network. Under a small gain assumption on the monotone operator induced by the gain matrix, a locally Lipschitz continuous ISS Lyapunov function is obtained constructively for the entire network by appropriately scaling the individualLyapunov functions for the subsystems.}},
  author       = {{Dashkovskiy, Sergey N. and Rüffer, Björn S. and Wirth, Fabian R.}},
  booktitle    = {{Proc. 51st IEEE Conf. Decis. Control}},
  pages        = {{4165–4170}},
  title        = {{{Small gain theorems for large scale systems and construction of ISS Lyapunov functions}}},
  year         = {{2012}},
}

@inproceedings{40835,
  abstract     = {{This work addresses the problem of deciding whether a set of realizations of a vector-valued time series with unknown temporal correlation are spatially correlated or not. Specifically, the spatial correlation is induced by a colored source over a frequency-flat single-input multiple-output (SIMO) channel distorted by independent and identically distributed noises with temporal correlation. The generalized likelihood ratio test (GLRT) for this detection problem does not have a closed-form expression and we have to resort to numerical optimization techniques. In particular, we apply the successive convex approximations approach which relies on solving a series of convex problems that approximate the original (non-convex) one. The proposed solution resembles a power method for obtaining the dominant eigenvector of a matrix, which changes over iterations. Finally, the performance of the proposed detector is illustrated by means of computer simulations showing a great improvement over previously proposed detectors that do not fully exploit the temporal structure of the source.}},
  author       = {{Ramírez, D. and Vía, J. and Santamaría, I. and Scharf, L. L.}},
  booktitle    = {{Proc.\ IEEE Int.\ Conf.\ Acoustics, Speech and Signal Process.}},
  title        = {{{Multiple-Channel Detection of a Gaussian Time Series over Frequency-Flat Channels}}},
  doi          = {{10.1109/ICASSP.2011.5947194}},
  year         = {{2011}},
}

@inproceedings{40834,
  abstract     = {{Spectrum sensing is a challenging key component of the Cognitive Radio paradigm, since primary signals must be detected in the face of noise uncertainty and at signal-to-noise ratios (SNRs) well below decodability levels. Multiantenna detectors exploit spatial independence of receiver thermal noise to boost detection performance and robustness. Here, we study the problem of detecting Gaussian signals with unknown rank-$P$ spatial covariance matrix when the noise at the receiver is independent across the antennas and with unknown power. A generic diagonal noise covariance matrix is allowed to model calibration uncertainties in the different antenna frontends. We derive the generalized likelihood ratio test (GLRT) for this detection problem. Although, in general, the corresponding statistic must be obtained by numerical means, in the low SNR regime the GLRT does admit a closed form. Numerical simulations show that the proposed asymptotic detector offers good performance even for moderate SNR values.}},
  author       = {{Ramírez, D. and Vazquez-Vilar, G. and López-Valcarce, R. and Vía, J. and Santamaría, I.}},
  booktitle    = {{Proc.\ IEEE Int.\ Conf.\ Acoustics, Speech and Signal Process.}},
  title        = {{{Multiantenna detection under noise uncertainty and primary user’s spatial structure}}},
  doi          = {{10.1109/ICASSP.2011.5946275}},
  year         = {{2011}},
}

@inproceedings{40833,
  abstract     = {{In this work, we derive a maximum likelihood formula for beamsteering in a multi-sensor array. The novelty of the work is that the impinging signal and noises are wide sense stationary (WSS) time series with unknown power spectral densities, unlike in previous work that typically considers white signals. Our approach naturally provides a way of fusing frequency-dependent information to obtain a broadband beamformer. In order to obtain the compressed likelihood, it is necessary to find the maximum likelihood estimates of the unknown parameters. However, this problem turns out to be an ML estimation of a block-Toeplitz matrix, which does not have a closed-form solution. To overcome this problem, we derive the asymptotic likelihood, which is given in the frequency domain. Finally, some simulation results are presented to illustrate the performance of the proposed technique. In these simulations, it is shown that our approach presents the best results.}},
  author       = {{Ramírez, D. and Vía, J. and Santamaría, I. and Scharf, L. L.}},
  booktitle    = {{Proc.\ IEEE Work.\ Stat.\ Signal Process.}},
  title        = {{{Multi-Sensor Beamsteering Based on the Asymptotic Likelihood for Colored Signals}}},
  doi          = {{10.1109/SSP.2011.5967644}},
  year         = {{2011}},
}

@inproceedings{40836,
  abstract     = {{In this paper we study the multiple-input multiple-output two-way relay channel (MIMO-TWRC) when the nodes use analog beamforming. Following the amplify-and-forward (AF) strategy, the problem consists of finding the transmit and receive beamformers of the nodes and the relay, and the power allocated to each one, that achieve the boundary of the capacity region. We express the optimal node beamformers in terms of the relay beamformers, and show that the capacity region can be efficiently characterized using convex optimization techniques. Numerical examples are provided to illustrate the results of this paper, and to compare the capacity region achieved by analog beamforming against the conventional MIMO schemes that operate at the baseband.}},
  author       = {{Lameiro, Christian and Nazábal, Alfredo and Gholam, Fouad and Vía, Javier and Santamaría, Ignacio}},
  booktitle    = {{Proc. Int. ICST Conf. Mobile Lightweight Wireless Syst.}},
  title        = {{{Capacity Region of the Two-Way Multi-Antenna Relay Channel with Analog Tx-Rx Beamforming}}},
  doi          = {{10.1007/978-3-642-29479-2_1}},
  year         = {{2011}},
}

@inproceedings{40828,
  abstract     = {{Spectrum sensing is a key component of the Cognitive Radio paradigm. Multiantenna detectors can exploit different spatial features of primary signals in order to boost detection performance and robustness in very low signal-to-noise ratios. However, in several cases these detectors require additional information, such as the rank of the spatial covariance matrix of the received signal. In this work we study the problem of estimating this rank under Gaussianity assumption using an uncalibrated receiver, i.e. with different (unknown) noise levels at each of the antennas.}},
  author       = {{Vazquez-Vilar, G. and Ramírez, D. and López-Valcarce, R. and Vía, J. and Santamaría, I.}},
  booktitle    = {{Proc. Int. Conf. on Cognitive Radio and Advanced Spectrum Management}},
  title        = {{{Spatial rank estimation in Cognitive Radio Networks with uncalibrated multiple antennas (invited paper)}}},
  doi          = {{10.1145/2093256.2093291}},
  year         = {{2011}},
}

@inproceedings{40837,
  abstract     = {{This paper considers linear precoding for time-varying multiple input multiple-output (MIMO) channels. We show that linear minimum mean-squared error (LMMSE) equalization based on the conjugate gradient (CG) method can result in significantly reduced complexity compared with conventional approaches. This reduction is achieved by incorporating a condition number constraint into the precoder optimization framework, which leads to clustered eigen values of the measurement covariance matrix. The cost is a small increase in MSE compared to the optimal precoder.}},
  author       = {{Tong, Jun and Schreier, Peter J. and Weller, Steven R. and Scharf, Louis L.}},
  booktitle    = {{Proc.\ IEEE Int.\ Conf.\ Acoustics, Speech and Signal Process.}},
  pages        = {{3092–3095}},
  title        = {{{Linear precoding for time-varying MIMO channels with low-complexity receivers}}},
  doi          = {{10.1109/ICASSP.2011.5946312}},
  year         = {{2011}},
}

@inproceedings{40830,
  abstract     = {{Interference Alignment (IA) has been revealed as one of the most attractive transmission techniques for the K-user in- terference channel. In this work, we employ a multiuser Multiple-Input Multiple-Output (MIMO) testbed to analyze, in realistic indoor scenarios, the impact of channel state information errors on the sum-rate performance of IA. We restrict our study to a 3-user interference network in which each user transmits a single data stream using two transmit and two receive antennas. For this MIMO interference network, only two different IA solutions exist. We also evaluate the performance gain obtained in practice by using the IA solution that maximizes the sum-rate.}},
  author       = {{García-Naya, J. A. and Castedo, L. and Ramírez, D. and Santamaría, I.}},
  booktitle    = {{Proc.\ Eur.\ Signal Process.\ Conf.}},
  title        = {{{Experimental Evaluation of Interference Alignment Under Imperfect Channel State Information}}},
  year         = {{2011}},
}

@inproceedings{40832,
  abstract     = {{This paper studies the design and analysis of large multiple-input multiple-output (MIMO) systems with linear precoding and Krylov subspace receivers. We design precoders that can improve performance with low-rank receivers. We then introduce a tool based on potential theory to analyze the convergence behavior of the mean-squared error (MSE). The effectiveness of the proposed precoder and the superexponential convergence of the MSE are demonstrated1.}},
  author       = {{Tong, Jun and Schreier, Peter J. and Weller, Steven R.}},
  booktitle    = {{Proc.\ IEEE Int.\ Symp.\ Inform.\ Theory}},
  pages        = {{2914–2918}},
  title        = {{{Precoder design and convergence analysis of MIMO systems with Krylov subspace receivers}}},
  doi          = {{10.1109/ISIT.2011.6034110}},
  year         = {{2011}},
}

@article{40831,
  abstract     = {{Spectrum sensing is a key component of the Cognitive Radio paradigm. Primary signals are typically detected with uncalibrated receivers at signal-to-noise ratios (SNRs) well below decodability levels. Multiantenna detectors exploit spatial independence of receiver thermal noise to boost detection performance and robustness. We study the problem of detecting a Gaussian signal with rank-$P$ unknown spatial covariance matrix in spatially uncorrelated Gaussian noise with unknown covariance using multiple antennas. The generalized likelihood ratio test (GLRT) is derived for two scenarios. In the first one, the noises at all antennas are assumed to have the same (unknown) variance, whereas in the second, a generic diagonal noise covariance matrix is allowed in order to accommodate calibration uncertainties in the different antenna frontends. In the latter case, the GLRT statistic must be obtained numerically, for which an efficient method is presented. Furthermore, for asymptotically low SNR, it is shown that the GLRT does admit a closed form, and the resulting detector performs well in practice. Extensions are presented in order to account for unknown temporal correlation in both signal and noise, as well as frequency-selective channels.}},
  author       = {{Ramírez, D. and Vazquez-Vilar, G. and López-Valcarce, R. and Vía, J. and Santamaría, I.}},
  journal      = {{{IEEE} {T}rans.\ {S}ignal\ {P}rocess.}},
  number       = {{8}},
  pages        = {{3764–3774}},
  title        = {{{Detection of rank-$P$ signals in Cognitive Radio Networks with uncalibrated multiple antennas}}},
  doi          = {{10.1109/TSP.2011.2146779}},
  volume       = {{59}},
  year         = {{2011}},
}