... Forecasting models 3.1 10 3.2 Time- varying VAR 12 3.3 Time- varying factor augmented VAR 14 3.4 Unobserved component model with stochastic volatility 15 3.5 Threshold and smooth transition VAR models ... Markov-switching VARs with joint switching in the coefficients and the covariance RSVARs** Markov-switching VARs with only the coefficients switching TVP-VAR (General) Time Varying VAR withtime varying ... (Standard) Time- varying VAR with constant degree of parameter drift TVP-VAR (Homoscedastic) Time- varying VAR with constant variance-covariance matrix of the VAR residuals TVP-FAVAR Time- varying...
... FCNNs withtimedelays in the leakage terms and distributed delays Motivated by the above discussions, the objective of this paper is to formulate and study impulsive BAM FCNNs withtimedelays ... networks withdelays Chaos Solitons Fractals 22, 773–785 (2004) doi:10.1016/j.chaos.2004.03.004 Feng, C, Plamondon, R: Stability analysis of bidirectional associative memory networks withtimedelays ... networks with time- varying delays Int J Syst Sci 41, 131–142 (2010) doi:10.1080/00207720903042921 25 Song, Q, Cao, J: Dynamical behaviors of discrete -time fuzzy cellular neural networks with variable...
... uniformly bounded for all time independent of the delays Also, the total solutions for admissible bounded controls are also bounded for all time independent of the delays 18 Fixed Point Theory ... paper is concerned with the positivity and stability of solutions independent of the sizes of the delays and also being independent of eventual coincidence of some values of delays if those ones ... concerned with the classical Riemann-Liouville differ-integration It is proved that the existence nonnegative solutions independent of the sizes of the delays and the stability properties of linear time- invariant...
... predator-prey system with feedback controls,” Applied Mathematics and Computation, vol 173, no 2, pp 694–709, 2006 11 F Chen, “Permanence of a discrete N-species cooperation system withtimedelays and ... the above question, we consider the following discrete n-species Schoener competition system withtimedelays and feedback controls: ⎧ ⎨ xi k xi k exp ri k − ⎩ xi k − τi k n bij k xj k − τj − ci ... Theorem 2.6 Now let us consider the following discrete N-species Schoener competition system withtime delays: ⎧ ⎨ xi k ri k − xi k exp ⎩ xi k − τi k n bij k xj k − τj − ci k j ⎫ ⎬ , ⎭ 2.44 1, ...
... ∗ v are given by (1.2) with either n0 = (continuous delays) or n0 = (continuous and discrete delays) or n0 = (discrete delays) Problem (3:1) is a special case of (1.1) with N = 2; (u1 ; u2 ) ... sense of Lyapunov stability) Moreover, for ÿnite continuous or discrete time delays, including the case r1 = r2 = without time delays, the constant (c1∗ ; c2∗ ) is globally asymptotically stable ... unstable For ÿnite continuous or discrete time delays, including the case without time delays, the stability property of (c1∗ ; c2∗ ) is global with respect to nontrivial nonnegative initial...
... delay differential equation with time- varying coefficients Appl Math Comput 2005;160:335–61 [14] Park JH Robust stabilization for dynamic systems with multiple time- varying delays and nonlinear uncertainties ... results for delayed neural networks withtime varying delays Physica D 2004;191:314–22 [24] Li Y Global exponential stability of BAM neural networks withdelays and impulses Chaos, Solitons & ... 2003;137:177–93 [9] Liang J, Cao J Exponential stability of continuous -time and discrete -time bidirectional associative memory networks withdelays Chaos, Solitons & Fractals 2004;22:773–85 [10] Huang L,...
... 59 4.2 Models of Subcutaneous Insulin 62 4.2.1 Compartmental Models 63 4.2.2 Non-Compartmental Models 69 4.3 Modeling Glucose-Insulin System with Subcutaneously-Injected ... residuals Therefore, lower order models can be estimated with a single set of glucose or insulin data, which is an advantage over larger models Three virtual patient models will be highlighted in ... Bergman, Sturis and Hovorka models are all PK models and used in following chapters All the three models have some common limitations although the structures of the models are different: The counter-regulatory...
... the importance of using models as tools to assist the policy analysis These models can be referred to as policy analysis models (Miser and Quade, 1985) or rapid assessment models (De Kok and Wind, ... basically functions of time The state (level) variables indicate the accumulation of a given quantity in the course of time; they express the result of integration If time stops, the level remains ... extent can such models contribute to our knowledge and ability to manage our environment? Are they useful and they have an added value in comparison with conventional process models? Centred...
... 'during that time' 'While' and 'as' are both usually used with the past continuous because the meaning of 'during that time' which indicates an action in progess By the time • • By the time he finished, ... here since 1987 'Since' means 'from that time' We use the present perfect (continuous) with 'since' 'Since' can also be used with a specific point in time As soon as • • He will let us know as ... also be used Whenever, every time • • Whenever he comes, we go to have lunch at "Dick's" We take a hike every time he visits 'Whenever' and 'every time' mean 'each time something happens' We use...
... Constrained Word Alignment Models The framework that we propose to incorporate statistical constraints into word alignment models is generic It can be applied to complicated models such IBM Model-4 ... indicating being a name or not Without these constraints, t-table entries for names with low frequency tend to be flat and word alignments can be chosen randomly without sufficient statistics or ... we assume that a name is produced by a name with a high probability but by a non-name with a low probability, i.e P (F = E) >> P (F = E), proper names with low counts then are encouraged to link...
... merits an operator notification Density WithTime Travel Without Time Travel 0.0 0.2 0.4 0.6 0.8 1.0 CPU utilization Figure 14: CPU load with and without Time Travel the TM, a NIDS can make fine-grained ... assumptions regarding time monotonicity For example, Bro derives its measure of time from the timestamps of the captured packets For example it uses these timestamps to compute timer expirations ... state The simple solution of rewriting the timestamps to reflect the current time confounds any analysis that relies on either absolute time or on relative time between multiple connections Such an...
... these models and scaling factors to a forced alignment, where we compute a phrase alignment for the training data From this alignment we then estimate new phrase models, while keeping all other models ... e e Table 1: Avg source phrase lengths in forced alignment without leaving-one-out and with standard and length-based leaving-one-out without l1o standard l1o length-based l1o To be able to perform ... singleton phrases are assigned the ˜ e probability β (|f |+|˜|) with the source and target 3.4 Parallelization To cope with the runtime and memory requirements of phrase model training that was...
... prediction by exploiting correlations within a single property cluster For example, if there are already many snippets with the attribute representing positive sentiment in a given property cluster, ... sentiment) dimensions Overall, the properties are correctly identified (subject of NEG matches the subject of POS) 68% of the time and a correct difference in attribute is identified 67% of the time ... whole collection of product review snippets, induces a set of learned properties, and models the aggregate user sentiment towards these properties We capture this idea using a Bayesian topic model...
... methods for hidden markov models: Theory and experiments with perceptron algorithms In Proceedings of EMNLP, pages 1–8 Jorge Nocedal 1980 Updating quasi-newton matrices with limited storage Mathematics ... conditional random fields with stochastic gradient methods In Proceedings of ICML, pages 969–976 Jun’ichi Kazama and Jun’ichi Tsujii 2003 Evaluation and extension of maximum entropy modelswith inequality ... to the point: 3.2 L1 regularization with cumulative penalty k Unfortunately, the clipping-at-zero approach does not solve all problems Still, we often end up with many features whose weights are...
... linear continuous operators from lp(0, ∞; X) to lp (0, ∞; Y ) Sometime, for the convenience of the formulation, we identify lp(s, t; X) with the space of all sequences (u(n))t n=s The truncated operators ... Kd) is called a solution of (4) with the initial value y(n0 ) = x0 if y(n + 1) = Bn y(n) + En A([F.y(·)]n0 )(n), n n0 (5) Suppose that (y(n)) is a solution of (4) with the initial value y(n0 ) ... Ilchmann, A.J Pritchard, Robustness of stability of time- varying linear systems, J Differential Equations, 82(1989) 219 [8] F Wirth, On the calculation of time- varying stability radii, Int J Robust Nonlinear...
... contributions We want to start with Edward Melomed: he inspired us, and we probably would not have started our journey with PowerPivot without a passionate discussion that we had with him several years ... DRM-free ebooks—use your ebooks across devices without restrictions or limitations Multiple formats—use on your laptop, tablet, or phone Lifetime access, with free updates Dropbox syncing—your files, ... the columns in the related table without needing to specify which ones (as was the case with VLOOKUP, which retrieved only a single column from the related table) With this new information, click...
... our t,emplate was to find an arbitrary sized rectangle within an image The rectangle had pixels with intensity specified by a Gaussian with mean and variance, pf and af, respectively Likewise, ... intensity specified by a Gaussian with pb and gb Our template was a rectangle specified by the coordinates of its upper-left and lower-right corners Starting with an initial template, estimates ... position of the rectangle, our system was always started with a rectangle that covered a majority of the input image (Figure 2) There is a problem with this procedure Consider The variable, X = (Xi...
... the BIC, among modelswith the same dimension, the one maximizing the likelihood is the optimum model with respect to both the AIC and BIC All analyses involving Weibull modelswith changepoints ... cumulative hazard of the Weibull model from the time origin up to time ti is H(t i ; z) = dependent on time The log cumulative hazard is also linear in both time and the covariates, i.e., log H(ti; ... hazard over time such as in the case of very high mortality hazard early after the start of ART We consider one such extension, which includes Weibull modelswith changepoints Weibull model with changepoints...