Stochastic stability analysis for the constant-modulus algorithm

We derive an easy-to-compute approximate bound for the range of step-sizes for which the constant-modulus algorithm (CMA) will remain stable if initialized close to a minimum of the CM cost function. Our model highlights the influence, of the signal constellation used in the transmission system: for smaller variation in the modulus of the transmitted symbols, the algorithm will be more robust, and the steady-state misadjustment will be smaller. The theoretical results are validated through several simulations, for long and short filters and channels.

Distributed power control algorithm for multiple access systems based on Verhulst model

In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.

A Separation Principle for the Continuous-Time LQ-Problem With Markovian Jump Parameters

In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

Comparing lock-in ranges and transient responses of second- and third-order phase-locked loops in master-slave clock distribution networks

The distribution of clock signals throughout the nodes of a network is essential for several applications. in control and communication with the phase-locked loop (PLL) being the component for electronic synchronization process. In systems with master-slave (MS) strategies, the PLLs are the slave nodes responsible for providing reliable clocks in all nodes of the network. As PLLs have nonlinear phase detection, double-frequency terms appear and filtering becomes necessary. Imperfections in filtering process cause oscillations around the synchronous state worsening the performance of the clock distribution process. The behavior of one-way master-slave (OWMS) clock distribution networks is studied and performances of first- and second-order filter processes are compared, concerning lock-in ranges and responses to perturbations of the synchronous state. (c) 2007 Elsevier GmbH. All rights reserved.

Linear minimum mean square filter for discrete-time linear systems with Markov jumps and multiplicative noises

In this paper we obtain the linear minimum mean square estimator (LMMSE) for discrete-time linear systems subject to state and measurement multiplicative noises and Markov jumps on the parameters. It is assumed that the Markov chain is not available. By using geometric arguments we obtain a Kalman type filter conveniently implementable in a recurrence form. The stationary case is also studied and a proof for the convergence of the error covariance matrix of the LMMSE to a stationary value under the assumption of mean square stability of the system and ergodicity of the associated Markov chain is obtained. It is shown that there exists a unique positive semi-definite solution for the stationary Riccati-like filter equation and, moreover, this solution is the limit of the error covariance matrix of the LMMSE. The advantage of this scheme is that it is very easy to implement and all calculations can be performed offline. (c) 2011 Elsevier Ltd. All rights reserved.

A generalized multi-period mean-variance portfolio optimization with Markov switching parameters

In this paper, we deal with a generalized multi-period mean-variance portfolio selection problem with market parameters Subject to Markov random regime switchings. Problems of this kind have been recently considered in the literature for control over bankruptcy, for cases in which there are no jumps in market parameters (see [Zhu, S. S., Li, D., & Wang, S. Y. (2004). Risk control over bankruptcy in dynamic portfolio selection: A generalized mean variance formulation. IEEE Transactions on Automatic Control, 49, 447-457]). We present necessary and Sufficient conditions for obtaining an optimal control policy for this Markovian generalized multi-period meal-variance problem, based on a set of interconnected Riccati difference equations, and oil a set of other recursive equations. Some closed formulas are also derived for two special cases, extending some previous results in the literature. We apply the results to a numerical example with real data for Fisk control over bankruptcy Ill a dynamic portfolio selection problem with Markov jumps selection problem. (C) 2008 Elsevier Ltd. All rights reserved.

Measurement Function Design for Visual Tracking Applications

Extracting human postural information from video sequences has proved a difficult research question. The most successful approaches to date have been based on particle filtering, whereby the underlying probability distribution is approximated by a set of particles. The shape of the underlying observational probability distribution plays a significant role in determining the success, both accuracy and efficiency, of any visual tracker. In this paper we compare approaches used by other authors and present a cost path approach which is commonly used in image segmentation problems, however is currently not widely used in tracking applications.

Context-free and context-sensitive dynamics in recurrent neural networks

Continuous-valued recurrent neural networks can learn mechanisms for processing context-free languages. The dynamics of such networks is usually based on damped oscillation around fixed points in state space and requires that the dynamical components are arranged in certain ways. It is shown that qualitatively similar dynamics with similar constraints hold for a(n)b(n)c(n), a context-sensitive language. The additional difficulty with a(n)b(n)c(n), compared with the context-free language a(n)b(n), consists of 'counting up' and 'counting down' letters simultaneously. The network solution is to oscillate in two principal dimensions, one for counting up and one for counting down. This study focuses on the dynamics employed by the sequential cascaded network, in contrast to the simple recurrent network, and the use of backpropagation through time. Found solutions generalize well beyond training data, however, learning is not reliable. The contribution of this study lies in demonstrating how the dynamics in recurrent neural networks that process context-free languages can also be employed in processing some context-sensitive languages (traditionally thought of as requiring additional computation resources). This continuity of mechanism between language classes contributes to our understanding of neural networks in modelling language learning and processing.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

An analysis of US greenhouse gas cap-and-trade proposals using a forward-looking economic model

We develop a forward-looking version of the recursive dynamic MIT Emissions Prediction and Policy Analysis (EPPA) model, and apply it to examine the economic implications of proposals in the US Congress to limit greenhouse gas (GHG) emissions. We find that shocks in the consumption path are smoothed out in the forward-looking model and that the lifetime welfare cost of GHG policy is lower than in the recursive model, since the forward-looking model can fully optimize over time. The forward-looking model allows us to explore issues for which it is uniquely well suited, including revenue-recycling and early action crediting. We find capital tax recycling to be more welfare-cost reducing than labor tax recycling because of its long-term effect on economic growth. Also, there are substantial incentives for early action credits; however, when spread over the full horizon of the policy they do not have a substantial effect on lifetime welfare costs.

Image reconstruction affects computer tomographic assessment of lung hyperinflation

Objectives: Lung hyperinflation may be assessed by computed tomography (CT). As shown for patients with emphysema, however, CT image reconstruction affects quantification of hyperinflation. We studied the impact of reconstruction parameters on hyperinflation measurements in mechanically ventilated (MV) patients. Design: Observational analysis. Setting: A University hospital-affiliated research Unit. Patients: The patients were MV patients with injured (n = 5) or normal lungs (n = 6), and spontaneously breathing patients (n = 5). Interventions: None. Measurements and results: Eight image series involving 3, 5, 7, and 10 mm slices and standard and sharp filters were reconstructed from identical CT raw data. Hyperinflated (V-hyper), normally (V-normal), poorly (V-poor), and nonaerated (V-non) volumes were calculated by densitometry as percentage of total lung volume (V-total). V-hyper obtained with the sharp filter systematically exceeded that with the standard filter showing a median (interquartile range) increment of 138 (62-272) ml corresponding to approximately 4% of V-total. In contrast, sharp filtering minimally affected the other subvolumes (V-normal, V-poor, V-non, and V-total). Decreasing slice thickness also increased V-hyper significantly. When changing from 10 to 3 mm thickness, V-hyper increased by a median value of 107 (49-252) ml in parallel with a small and inconsistent increment in V-non of 12 (7-16) ml. Conclusions: Reconstruction parameters significantly affect quantitative CT assessment of V-hyper in MV patients. Our observations suggest that sharp filters are inappropriate for this purpose. Thin slices combined with standard filters and more appropriate thresholds (e.g., -950 HU in normal lungs) might improve the detection of V-hyper. Different studies on V-hyper can only be compared if identical reconstruction parameters were used.

A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography

Little consensus exists in the literature regarding methods for determination of the onset of electromyographic (EMG) activity. The aim of this study was to compare the relative accuracy of a range of computer-based techniques with respect to EMG onset determined visually by an experienced examiner. Twenty-seven methods were compared which varied in terms of EMG processing (low pass filtering at 10, 50 and 500 Hz), threshold value (1, 2 and 3 SD beyond mean of baseline activity) and the number of samples for which the mean must exceed the defined threshold (20, 50 and 100 ms). Three hundred randomly selected trials of a postural task were evaluated using each technique. The visual determination of EMG onset was found to be highly repeatable between days. Linear regression equations were calculated for the values selected by each computer method which indicated that the onset values selected by the majority of the parameter combinations deviated significantly from the visually derived onset values. Several methods accurately selected the time of onset of EMG activity and are recommended for future use. Copyright (C) 1996 Elsevier Science Ireland Ltd.

Risk attitude, planting conditions and the value of seasonal forecasts to a dryland wheat grower

The value of a seasonal forecasting system based on phases of the Southern Oscillation was estimated for a representative dryland wheat grower in the vicinity of Goondiwindi. In particular the effects on this estimate of risk attitude and planting conditions were examined. A recursive stochastic programming approach was used to identify the grower's utility-maximising action set in the event of each of the climate patterns over the period 1894-1991 recurring In the imminent season. The approach was repeated with and without use of the forecasts. The choices examined were, at planting, nitrogen application rate and cultivar and, later in the season, choices of proceeding with or abandoning each wheat activity, The value of the forecasting system was estimated as the maximum amount the grower could afford to pay for its use without expected utility being lowered relative to its non use.

Pre- and postnatal exposure to ambient levels of urban particulate matter (PM(2.5)) affects mice spermatogenesis

This work characterizes the effects of ambient levels of urban particulate matter (PM(2.5)) from the city of Sao Paulo on spermatogenesis using mice exposed during the embryo-fetal and/or postnatal phases of development. Parental generations (BALB/c mice) were exposed to air pollution in chambers with or without filtering PM(2.5) for 4 months. Animals were mated, and half of the 1-day-old offspring were moved between chambers, which yielded prenatal and postnatal groups. Remaining offspring comprised the non-exposed and pre+postnatal exposed groups. After 90 days, the animals were sacrificed for testis collection and weighing. Optical microscopy was used for the morphometric analyses of the cell counts, spermatogenic cycle, proliferation, and apoptosis. Prenatally exposed animals presented reduced body and testicular weight with an increased gonadosomatic index (GSI). Testicular volume also decreased, as well as the tubular diameter in testes of the same animals. Proliferation, apoptosis, and spermatogenic cycle analyses showed no significant differences among groups. However, the tubules at stage VII of pre- and postnatal animals presented a reduced number of elongated spermatids. Pre+postnatal group presented higher spermatid head retention at stages VIII-XII. These results show that ambient levels of PM(2.5) from Sao Paulo city affect spermatogenesis by damaging sperm production.

The `club` cell and behavioural and physiological responses to chemical alarm cues in the Nile tilapia

The alarm response to skin extract has been well documented in fish. In response to skin extract, there is a decline in both locomotion activity and aggressive interactions. Our observation herein of these responses in the cichlid Nile tilapia, Oreochromis niloticus, confirmed the existence of the alarm response in this species. However, so far there has been a paucity of information on the autonomic correlates of this response. In this study, the ventilatory change in response to the chemical alarm cue was evaluated. This parameter was measured 4 min before and 4 min after exposure to 1 mL of either conspecific skin extract or distilled water (extract vehicle). Skin extract induced an increase in the ventilation rate, which suggested an anticipatory adjustment to potentially harmful stimuli. The chemical cue (alarm substance) also interfered with the prioritisation of responses to different environmental stimuli (stimuli filtering); this was suggested by the observation that the Nile tilapia declined to fight after exposure to a cue that indicates a risk of predation. Furthermore, histological analysis of the Nile tilapia skin revealed the presence of putative alarm substance-producing (club) cells.