... Signal Processing and the respective inner iterations are three and two in the first and second outer iterations, and one in the others Figure 3(d) presents the final group-delay errors, and the errors ... maximally flat and weighted -least- squares variable fractional-delay filters,” IEEE Transactions on Circuits and Systems I, vol 54, no 12, pp 2718–2732, 2007 [11] J J Shyu, S C Pei, C H Chan, and Y D ... 1557–1564, 1987 [27] M Lang and T I Laakso, “Simple and robust method for the design of allpass filters using least- squares phase error criterion,” IEEE Transactions on Circuits and Systems II, vol 41,...
... kurtosis, and the delay statistics are evaluated using the mean excess delay and the root mean square (rms) delay spread of the received MPCs And third, to analyze different weighted least- squares ... mean and standard deviation of In(τ m ) and In(τ rms ) as well as the K-S passing rates are tabulated in Table 2, and their corresponding PDFs are depicted ˙ Ismail G¨ venc et al u ¸ in Figures and ... Correlation coefficient between two random variables R1 and R2 is given by ρR1 ,R2 = (E(R1 R2 ) − E(R1 )E(R2 ))/σ R1 σ R2 , where σ R1 and σ R2 are the standard deviations of R1 and R2 , respectively (13)...
... these two modified algorithms are referred to as the quadratic correction leastsquares (QCLS) and linear correction leastsquares (LCLS), respectively Recently, we have improved [18] the performance ... Processing Table 1: List of abbreviations and symbols AOA Angle-of-arrival CWLS Constrained weighted leastsquares CRLB Cram´ r-Rao lower bound e NLS Nonlinear leastsquares RSS Received signal strength ... constrained weighted leastsquares (CWLS)/weighted leastsquares (WLS) mobile location approach for time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival...
... scientific and engineering papers and contributed to organizing several conferences and workshops He is an AES Fellow and Silver Medalist as well as Member of IEEE (Institute of Electrical and Electronics ... sets; (b) phase functions and phase derivatives; (c) on log-scale; and (d) in dB on log-scale all pass filter we have utilized an iterative procedure proposed by Brandenstein and Unbehauen [25], which ... lines in the middle of the figure) and R = 0.03 (see (15b)) After lowand high-frequency roll-off compensations to avoid boosting off-bands of the speaker, as shown by Curve (c), the EQ filter resulting...
... other regulators, and rarely act independently Partial leastsquares regression Here we propose to employ the method of partial leastsquares regression [15] to infer true TFAs and the functional ... NL: Canonical partial leastsquaresand continuum power regression J Chemometrics 2001, 15:85-100 Datta S: Exploring relationships in gene expressions: a partial leastsquares approach Gene Expression ... point time point Figure for the E Coli (top and middle row) and Spellman (bottom row) data sets Y-loadings Y-loadings for the E Coli (top and middle row) and Spellman (bottom row) data sets each...
... recursive least- squares (RLS) algorithms and the corresponding fast versions (known as FTF and FAEST), QR and inverse QR algorithms, least- squares lattice (LSL), and QR decomposition-based least- squares ... recursive least- squares algorithms (FTF and FAEST) were independently derived in [11] Carayannis, G., Manolakis, D., and Kalouptsidis, N., A fast sequential algorithm for leastsquares filtering and ... as in (21.23) 21.4 The Recursive Least- Squares Problem The recursive least- squares formulation deals with the problem of updating the solution w of a leastsquares problem (regularized or not)...
... LDI -Exact (here, exact means the n is big enough, e.g., n = 10K), the BMP, and the BHP on DPLVM mod- Results and Discussions 5.1 Bio-NER Figure shows the F-measure, exactitude, #latentpath and ... texts Proceedings of EMNLP’02 John Lafferty, Andrew McCallum, and Fernando Pereira 2001 Conditional random fields: Probabilistic models for segmenting and labeling sequence data Proceedings of ICML’01, ... Speech and Signal Processing, v1:532–535 V Goel and W Byrne 2000 Minimum bayes-risk automatic speech recognition Computer Speech and Language, 14(2):115–135 779 P.E Hart, N.J Nilsson, and B Raphael...
... linear interpolation and one uses cubicspline functions for interpolation, we can see an advantage of the latter: the cubicspline functions give smoother curve of profiles, and the profiles reflect ... the horizons 0, 10, 20, 30, 50, 75, 100, 125, 150, 200, 250, 300, 400, 500, 600, 800 and 1000m Using the cubicspline functions, we computed the temperature values at different a1 a2 a3 24.88 24.89 ... surface to 1000m, and the result gives us the cubic polynomials at the intervals [ z0 , z1 ], [ z1 , z2 ], , (5) T − T T − T Fk = 3 k −1 k − k k +1 , hk +1 hk k = 1, 2, , n and: hk = xk...
... linear interpolation and the interpolation using cubicspline functions, we can see the advantage of the later one The cubicspline functions give smoother curve of profiles and the profiles reflect ... 600, 800 and 1000 m Using the cubicspline functions we have computed the temperature values from the surface layer to the 1000 m layer at different layer of distance m will gives us the cubic polynomials ... "Hydrometeoizdat", Leningrad, 134 p (in Russian) Schoenberg I, J., 1964 Spline function and the problem of graduation Pro Nat USA Sử dụng hm spline bậc ba để tính trắc diện thẳng đứng nhiệt độ nớc biển...
... order and investigate the generalized Hyers-Ulam-Rassias stability and the superstability by using the alternative fixed point for cubic functional Equation (1.2) and their correspondent cubic ... (3:7) The proof of Theorem 2.2 shows that T is a cubic mapping If we substitute z and w by 2nz and 2nw in (3.1), respectively, and put x = y = and we divide the both sides of the obtained inequality ... Bodaghi et al.: Approximately cubic functional equations andcubic multipliers Journal of Inequalities and Applications 2011 2011:53 Submit your manuscript to a journal and benefit from: Convenient...
... order and investigate the generalized Hyers-Ulam-Rassias stability and the superstability by using the alternative fixed point for cubic functional Equation (1.2) and their correspondent cubic ... (3:7) The proof of Theorem 2.2 shows that T is a cubic mapping If we substitute z and w by 2nz and 2nw in (3.1), respectively, and put x = y = and we divide the both sides of the obtained inequality ... Bodaghi et al.: Approximately cubic functional equations andcubic multipliers Journal of Inequalities and Applications 2011 2011:53 Submit your manuscript to a journal and benefit from: Convenient...
... 2.27 6fe 2x y y 2fe 2x − y − 12fe x − 3fe y 2.28 and interchanging x and y yields fe 4x y 4fe x y By adding 2.27 and 2.28 and then using 2.25 and 2.26 , we lead to fe x 4y fe 4x y 32fe x 24fe ... by letting A x − 1/6 Ao x , and C x x ∈ X To prove the uniqueness of A and C, let A1 , C1 : X → Y be another additive andcubic maps satisfying 3.29 Let A A − A1 , and let C C − C1 So A x −C ... functions,” Abstract and Applied Analysis, vol 2008, Article ID 801904, 17 pages, 2008 33 M E Gordji and H Khodaei, “Solution and stability of generalized mixed type cubic, quadratic and additive functional...
... signal transmission model and the channel model are introduced In Section 3, the leastsquares algorithm is derived and extended as a joint blind channel detection and estimation algorithm In ... Doppler frequency of the pth path channel THE BLIND RECURSIVE LEASTSQUARES JOINT DETECTION AND ESTIMATION In Appendix A, recursive leastsquares algorithm is derived for the estimation of the MIMO ... normalized power for training and data bits are assumed In all simulations, receiver antennas andand transmitter antennas are considered that correspond to × (half rank) and × (full rank) MIMO channels...
... w(n), , w(n) , (22) The superscripts ∗ and H stand for conjugation and conjugate transposition, respectively The notations “re” and “im” stand for the real and imaginary parts, respectively Non-Data-Aided ... Swami, and A K Nandi, “Non-linear leastsquares estimation for harmonics in multiplicative and additive noise,” Signal Processing, vol 78, no 1, pp 43–60, 1999 [5] M Ghogho, A Swami, and T Durrani, ... + τ) e− j2παn e− j2π f τ , k=0 ˙ J(θ) := and S2e (α; f ) and S2e (α; f ) stand for the unconjugate and conjugate cyclic spectra of e(n) at cycle α and frequency f , defined as S2e (α; f ):= k...
... response performance Leastsquaresand minimax (equiripple) stopbands can be obtained using the PCLS methods described in [6, 7, 8, 9] Neither leastsquares nor minimax stopbands are effective at ... passband for the filters with the hardware cost of 1144 and 668 LEs for Adams’ filter (95 taps, passband ripple = dB, passband cutoff = 0.125π rad, stopband cutoff = 0.1608π rad, and minimum stopband ... cost and PSR results for proposed rapid prototyping design method for Adams’ filter (95 taps, passband ripple = dB, passband cutoff = 0.125π rad, stopband cutoff = 0.1608π rad, and minimum stopband...
... in i and j: Fij = α, Fij = β There are two cases to examine: Case X = X : Then λ > and so µ > Choose any j (1 ≤ j ≤ µm) Let Yα and Yβ meet the line Lj at Ljt and Lju , respectively In Γ, Xt and ... exactly λ parallel classes We say two lines are parallel if they are parallel to the same λ parallel classes It is well known and easy to prove that a line L has at most m points; and L has exactly ... 1)2 /(m − 1) squares The set is complete if it has this many squares According to [2], the only complete sets of MOFS known are of type F (n, µ) with either: (i) m a prime power and n a power...
... det(M) (3) and The moments of traces were studied by Diaconis and Shahshahani [23] and Diaconis and Evans [21] who proved the following result: Theorem (a) Consider a = (a1 , , al ) and b = (b1 ... nonnegative integers and whose rows and columns sum up to the same number j The number of magic squares of order k with row and column sum j, denoted by Hk (j), is of great interest; see [22] and references ... graph and let p(G) be the total number of matchings in G Let X be the random variable whose value is the number of edges in a randomly chosen matching; denote by m(G) its mean and by σ(G) its standard...
... segment F M The triangles ∆1 and ∆3 we triangulate into at1 and at3 triangles of equal areas by placing at1 − and at3 − vertices equidistantly on the line segments AB and DC, respectively This yields ... satisfying the conditions (i), (ii), and (iii) Then {Tni }i≥0 gives rise to sequences {Tn′i }i≥0 and {Tn′′ }i≥0 of triangulations of the i triangles ∆1 and ∆2 into n′i and n′′ triangles, respectively ... D1 and the area of D2 is at least A1 A2 − ′′ , n′i ni because the maximum over all differences between the area of a triangle in Tn′i and the area of a triangle in Tn′′ is minimal if both ∆1 and...
... (breeding values) of animals with records in y,, random with mean zero and variance A and a;, l i e is the vector of residuals, random with mean zero and variance Iu’ i is The breeding value of the ... with order and rank leastsquares solution to generalized with one (13) equal to the rank of X, q is the solution to or, equivalently, or, equivalently, That b is the generalized leastsquares solution ... (1980) If y ; and the model becomes the reduced animal model of QuAAs and contains only daughter records and a contains only male breeding i values, then suitable redefinition of e T,, and D generates...
... cubic spline, quartic spline, exponential splineand new quartic smoothing function Details on weight functions will be discussed in the following section when we introduce the Moving Least- Squares ... novel meshfree smoothed least- squares (SLS) method 45 2.1 Introduction 45 2.2 Meshfree smoothed least- squares (SLS) formulation 47 2.2.1 General least- squares formulations ... (Atluri and Zhu, 2000), 4th order thin beams (Atluri et al., 1999a) and thick beams (Cho and Atluri, 2001), linear fracture problems (Ching and Batra, 2001), fluid mechanics problems (Lin and Atluri,...