ORIGIN-DESTINATION MATRIX ESTIMATION METHODS.

of multiple periodic signals in noise. First, we state theproblem mathematically in Sect. II and introduce someuseful notation and results after which we present, inSect. III, some classical methods for solving the afore-mentioned problem. These are intimately related to themethods under cons[r]

Hindawi Publishing CorporationEURASIP Journal on Advances in Signal ProcessingVolume 2007, Article ID 57354, 13 pagesdoi:10.1155/2007/57354Research ArticleArray Processing and Fast Optimization Algorithms forDistorted Circular Contour RetrievalJulien Marot and Salah BourennaneGSM, Institut Fresnel,[r]

, and thus it can only be usedA,si(t),ESTIMATION OF THE MIXING MATRIX309in small dimensions. Suitable approximations of the algorithm might alleviate thislimitation [19].A very different approximation of the likelihood method was derived in [195],in which a form of competitive neural l[r]

means of computing the weights of an optimal beamformercapable of maximizing the signal-to-interference plus noiseratio (SINR) in a coherent environment. EVESPA has alsobeen considered in [3] under a slight variation for t heproblem of direction of arrival (D OA) estimation in mobilecommunica[r]

transform (linear model) and Taylor series (Michaelis–Menten kinetics), we refer to Godfrey and Fitch [18].Another classic method is the similarity transformationapproach [19–21]. These two methods have been com-pared without a decisive preference [22]. Recently,methods were developed[r]

Hindawi Publishing CorporationEURASIP Journal on Advances in Signal ProcessingVolume 2010, Article ID 973286, 7 pagesdoi:10.1155/2010/973286Research ArticleTime-Frequency Based Channel Estimat ion for High-MobilityOFDM Systems—Part II: Cooperative Relaying CaseErol¨Onen, Niyazi Odabas¸io˘glu, and Ay[r]

240KALMAN FILTER ENGINEERING8.2.1.2 Operations per Cycle Factors that in¯uence the numbers of arith-metic operations per cycle of a Kalman ®lter implementation on a speci®capplication include the following:1. The dimensions of the state vector x (n), measurement vector z (`), andprocess noise vector[r]

lize, in general, the information contained in the data vectors. On the other hand,these methods have some advantages. They will be discussed in more detail inChapter 11, and related methods can be found in Chapter 8 as well.4.4 LEAST-SQUARES ESTIMATION4.4.1 Linear least-squares[r]

Hindawi Publishing CorporationEURASIP Journal on Advances in Signal ProcessingVolume 2009, Article ID 104950, 21 pagesdoi:10.1155/2009/104950Research ArticleLimited Feedback Multiuser MIMO Techniques forTime-Correlated ChannelsEduardo Zacar´ıas B, Stefan Werner, and Risto WichmanDepartment of Signal[r]

(16.9)which means that the rows of form an orthonormal system. This orthonormalitycould be enforced after every step of (16.8), for further stabilization.16.2.2 Maximizing likelihood approximationsMaximization of the joint likelihood is a rather crude method of estimation. Froma Bayesian view[r]

Hindawi Publishing CorporationEURASIP Journal on Advances in Signal ProcessingVolume 2007, Article ID 12172, 14 pagesdoi:10.1155/2007/12172Research ArticleBlind Identification of FIR Channels in the Presence ofUnknown NoiseXiaojuan He and Kon Max WongDepartment of Electrical and Computer Engineering,[r]

Task Space Approach of Robust Nonlinear Control for a 6 DOF Parallel Manipulator Hag Seong Kim Agency for Defense Development Korea 1. Introduction The dynamics and kinematics of a parallel manipulator has been widely researched by virtue of its a high force-to-weight ratio and widespread applicatio[r]

~ 0.5 h). The duration ofthe effect can be prolonged by:1. Use of higher doses, enabling plas-ma levels to remain above the minimal-ly effective antibacterial concentration;2. Combination with probenecid. Re-nal elimination of penicillin occurschiefly via the anion (acid)-secretorysystem of the prox[r]

For the network impedance estimation application, it has been found that the energy level for ΔI(f) is a useful data filtering, but for ΔV(f) it has been found that it does not really make any difference. The Coherence index does not reveal much information about unreliable measurements but c[r]

The problem of estimating relative time delay asso-ciated with a signal source and a pair of spatially sepa-rated microphones has been extensively studied [7-15].Among TDE methods, the generalized cross-correlation(GCC) method is one of the most widely used becauseof its simplicity and accept[r]

0, and Wiis the T ÂMsubmatrix of Xiobtained by removing the time-constant variables, is identical to therandom e¤ects estimator. The column dimension of matrix (11.58) is only K þ M,sothere are only M overidentifying restrictions in using the 3SLS estimator.The algebraic equivalence between 3[r]

be a normal random variable with mean zero and variance a-2 • Althoughthe residuals12e have expected value O, their covariance matrix a- [ I - Z (Z' Z ) - Z ' ] = a-2 [I - H]is not diagonal. Residuals have unequal variances and nonzero correlations. Fortu­nately, the correlations are often sm[r]

the mutual contraction of an edge e(u, v) requires O[deg(u) +deg(v)]time, where deg(x) representsthe degree of node x. However, although mutual contraction is asymptotically more expensive thannetlength computations, it is usually faster in practice because its use in technology mapping doesnot requ[r]

2042 ✦ Chapter 31: The UCM Procedureif the model is stationary or if the model is nonstationary and there are no missing values in thedata. See Chapter 7, “The ARIMA Procedure,” for additional details about the ARIMA procedure.However, if there are missing values in the data and the model is nonstat[r]

of the project.During the course of the development, progress of the project is monitored andcompared with the Pert diagram. Should any stage take longer or shorter than planned,the diagram is updated to reflect the new situation.At the outset of a project, the requirements for the system are usuall[r]