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1.
Let m and vt, 0 ? t ? 2π be measures on T = [0, 2π] with m smooth. Consider the direct integral H = ⊕L2(vt) dm(t) and the operator (L?)(t, λ) = e?iλ?(t, λ) ? 2e?iλtT ?(s, x) e(s, t) dvs(x) dm(s) on H, where e(s, t) = exp ∫stTdvλ(θ) dm(λ). Let μt be the measure defined by T?(x) dμt(x) = ∫0tT ?(x) dvs dm(s) for all continuous ?, and let ?t(z) = exp[?∫ (e + z)(e ? z)?1t(gq)]. Call {vt} regular iff for all t, ¦?t(e)¦ = ¦?(e for 1 a.e.  相似文献   

2.
Let G be a semisimple noncompact Lie group with finite center and let K be a maximal compact subgroup. Then W. H. Barker has shown that if T is a positive definite distribution on G, then T extends to Harish-Chandra's Schwartz space C1(G). We show that the corresponding property is no longer true for the space of double cosets K\GK. If G is of real-rank 1, we construct liner functionals Tp ? (Cc(K\GK))′ for each p, 0 < p ? 2, such that Tp(f 1 f1) ? 0, ?f ? Cc(K\GK) but Tp does not extend to a continuous functional on Cp(K\GK). In particular, if p ? 1, Tv does not extend to a continuous functional on C1(K\GK). We use this to answer a question (in the negative) raised by Barker whether for a K-bi-invariant distribution T on G to be positive definite it is enough to verify that T(f 1 f1) ? 0, ?f ? Cc(K\GK). The main tool used is a theorem of Trombi-Varadarajan.  相似文献   

3.
The operator L?(t, λ) = e?iλ(t, λ) ? 2e?iλtT?(s, x) e(s, t) dvs(x) dm(s) acting on H=∝02πL2(vt), where m and vt, 0 ? t ? 2π are measures on [0, 2π] with m smooth and e(s, t) = exp[?∝tsTdvλ(θ) dm(λ)], satisfies rank(I ? LL1) = rank(I ? L1L) = 1. It is, therefore, unitarily equivalent to a scalar Sz.-Nagy-Foia? canonical model. The purpose of this paper is to determine the model explicitly and to give a formula for the unitary equivalence.  相似文献   

4.
For a given score function ψ = ψ(x, θ), let θn be Huber's M-estimator for an unknown population parameter θ. Under some mild smoothness assumptions it is known that n12n ? θ) is asymptotically normal. In this paper the stopping times τc(m) = inf{n ≥ m: n12n ? θ | > c } associated with the sequence of confidence intervals for θ are investigated. A useful representation of M-estimators is derived, which is also appropriate for proving laws of the iterated logarithm and Donskertype invariance principles for (πn)n.  相似文献   

5.
This paper is a study of the distribution of eigenvalues of various classes of operators. In Section 1 we prove that the eigenvalues (λn(T)) of a p-absolutely summing operator, p ? 2, satisfy
n∈Nn(T)|p1pp(T).
This solves a problem of A. Pietsch. We give applications of this to integral operators in Lp-spaces, weakly singular operators, and matrix inequalities.In Section 2 we introduce the quasinormed ideal Π2(n), P = (p1, …, pn) and show that for TΠ2(n), 2 = (2, …, 2) ∈ Nn, the eigenvalues of T satisfy
i∈Ni(T)|2nn2n2(T).
More generally, we show that for TΠp(n), P = (p1, …, pn), pi ? 2, the eigenvalues are absolutely p-summable,
1p=i=1n1piandn∈Nn(T)|p1p?CpπnP(T).
We also consider the distribution of eigenvalues of p-nuclear operators on Lr-spaces.In Section 3 we prove the Banach space analog of the classical Weyl inequality, namely
n∈Nn(T)|p ? Cpn∈N αn(T)p
, 0 < p < ∞, where αn denotes the Kolmogoroff, Gelfand of approximation numbers of the operator T. This solves a problem of Markus-Macaev.Finally we prove that Hilbert space is (isomorphically) the only Banach space X with the property that nuclear operators on X have absolutely summable eigenvalues. Using this result we show that if the nuclear operators on X are of type l1 then X must be a Hilbert space.  相似文献   

6.
Let α(n1, n2) be the probability of classifying an observation from population Π1 into population Π2 using Fisher's linear discriminant function based on samples of size n1 and n2. A standard estimator of α, denoted by T1, is the proportion of observations in the first sample misclassified by the discriminant function. A modification of T1, denoted by T2, is obtained by eliminating the observation being classified from the calculation of the discriminant function. The UMVU estimators, T11 and T21, of ET1 = τ1(n1, n2) and ET2 = τ2(n1, n2) = α(n1 ? 1, n2) are derived for the case when the populations have multivariate normal distributions with common dispersion matrix. It is shown that T11 and T21 are nonincreasing functions of D2, the Mahalanobis sample distance. This result is used to derive the sampling distributions and moments of T11 and T21. It is also shown that α is a decreasing function of Δ2 = (μ1 ? μ2)′Σ?11 ? μ2). Hence, by truncating T11 and T21 (or any estimator) at the value of α for Σ = 0, new estimators are obtained which, for all samples, are as close or closer to α.  相似文献   

7.
Si studia, in un cilindro, il problema di Dirichlet per l'equazione ellittica del II ordine: Lαu = ?, dove Lα = αΔ + (1 ? 3α)∑ij = 12 xixj(x12 + x22)?1?2?xi?xj, α ? (0, 13]è l'operatore a coefficienti discontinui sull'asse x3 già introdotto da N. Ural'tseva per mostrare che l'equazione considerata può non avere soluzione nello spazio di Sobolev W2,p(p > 2) per qualche f?Lp. In questo lavoro si danno limitazioni a priori e teoremi di esistenza e unicità in W2,p quando p varia in un intervallo (p1(α), p2(α)), dipendente dalla costante di ellitticità α. Se p = p2(α) le limitazioni a priori cadono: l'esempio è quello di Ural'tseva.  相似文献   

8.
Necessary and sufficient conditions are proved for a b(2)-Young function G (with independent variable t) to be convex (resp. concave) in t2 in terms of inequalities between the second derivative of G and the first derivative of its Legendre transform G? (with independent variable s). It is then proven that a Young function G is convex (resp. concave) in t2 if and only if G? is concave (resp. convex) in s2. These results, along with another set of inequalities for functions G convex (resp. concave) in t2, allow the proof of the uniform convexity and thereby of the reflexivity with respect to Luxemburg's norm ∥f∥G = inf{k > 0: ∝Ω dξ G(f(ξ)k) ? 1} of the Orlicz space LG(Ω) over an open domain Ω ?RN with Lebesgue measure . When applied to G(t) = ¦t¦pp and G?(s) = ¦s¦p′p′ with p?1 + (p′)?1 = 1, the preceding results lead to the shortest proof to date of two Clarkson's inequalities and of the reflexivity of Lp-spaces for 1 < p < +∞. Finally, some of these results are used to solve by direct methods variational problems associated with the existence question of periodic orbits for a class of nonlinear Hill's equations; these variational problems are formulated on suitable Orlicz-Sobolev spaces WmLG(Ω) and thereby allow for nonlinear terms which may grow faster than any power of the variable.  相似文献   

9.
For any prime p, the sequence of Bell exponential numbers Bn is shown to have p ? 1 consecutive values congruent to zero (mod p), beginning with Bm, where m ≡ 1 ? (pp ? 1)(p ? 1)2 (mod(pp ? 1)(p ? 1)). This is an improvement over previous results on the maximal strings of zero residues of the Bell numbers. Similar results are obtained for the sequence of generalized Bell numbers An generated by e?(ex ? 1) = Σn = 0 Anxnn!.  相似文献   

10.
Given a set S of positive integers let ZkS(t) denote the number of k-tuples 〈m1, …, mk〉 for which mi ∈ S ? [1, t] and (m1, …, mk) = 1. Also let PkS(n) denote the probability that k integers, chosen at random from S ? [1, n], are relatively prime. It is shown that if P = {p1, …, pr} is a finite set of primes and S = {m : (m, p1pr) = 1}, then ZkS(t) = (td(S))k Πν?P(1 ? 1pk) + O(tk?1) if k ≥ 3 and Z2S(t) = (td(S))2 Πp?P(1 ? 1p2) + O(t log t) where d(S) denotes the natural density of S. From this result it follows immediately that PkS(n) → Πp?P(1 ? 1pk) = (ζ(k))?1 Πp∈P(1 ? 1pk)?1 as n → ∞. This result generalizes an earlier result of the author's where P = ? and S is then the whole set of positive integers. It is also shown that if S = {p1x1prxr : xi = 0, 1, 2,…}, then PkS(n) → 0 as n → ∞.  相似文献   

11.
It is known that the classical orthogonal polynomials satisfy inequalities of the form Un2(x) ? Un + 1(x) Un ? 1(x) > 0 when x lies in the spectral interval. These are called Turan inequalities. In this paper we will prove a generalized Turan inequality for ultraspherical and Laguerre polynomials. Specifically if Pnλ(x) and Lnα(x) are the ultraspherical and Laguerre polynomials and Fnλ(x) = Pnλ(x)Pnλ(1), Gnα(x) = Lnα(x)Lnα(0), then Fnα(x) Fnβ(x) ? Fn + 1α(x) Fn ? 1β(x) > 0, ? 1 < x < 1, ?12 < α ? β ? α + 1 and Gnα(x) Gnβ(x) ? Gn + 1α(x) Gn ? 1β(x) > 0, x > 0, 0 < α ? β ? α + 1. We also prove the inequality (n + 1) Fnα(x) Fnβ(x) ? nFn + 1α(x) Fn ? 1β(x) > An[Fnα(x)]2, ?1 < x < 1, ?12 < α ? β < α + 1, where An is a positive constant depending on α and β.  相似文献   

12.
Let V be a set of n points in Rk. Let d(V) denote the diameter of V, and l(V) denote the length of the shortest circuit which passes through all the points of V. (Such a circuit is an “optimal TSP circuit”.) lk(n) are the extremal values of l(V) defined by lk(n)=max{l(V)|VVnk}, where Vnk={V|V?Rk,|V|=n, d(V)=1}. A set VVnk is “longest” if l(V)=lk(n). In this paper, first some geometrical properties of longest sets in R2 are studied which are used to obtain l2(n) for small n′s, and then asymptotic bounds on lk(n) are derived. Let δ(V) denote the minimal distance between a pair of points in V, and let: δk(n)=max{δ(V)|VVnk}. It is easily observed that δk(n)=O(n?1k). Hence, ck=lim supn→∞δk(n)n1k exists. It is shown that for all n, ckn?1k≤δk(n), and hence, for all n, lk(n)≥ ckn1?1k. For k=2, this implies that l2(n)≥(π212)14n12, which generalizes an observation of Fejes-Toth that limn→∞l2(n)n?12≥(π212)14. It is also shown that lk(n) ≤ [(3?√3)k(k?1)]nδk(n) + o(n1?1k) ≤ [(3?√3)k(k?1)]n1?1k + o(n1?1k). The above upper bound is used to improve related results on longest sets in k-dimensional unit cubes obtained by Few (Mathematika2 (1955), 141–144) for almost all k′s. For k=2, Few's technique is used to show that l2(n)≤(πn2)12 + O(1).  相似文献   

13.
14.
Let D(?) be the Doob's class containing all functions f(z) analytic in the unit disk Δ such that f(0) = 0 and lim inf¦f(z) ¦ ? 1 on an arc A of ?Δ with length ¦A ¦? ?. It is first proved that if f?D(?) then the spherical norm ∥ f ∥ = supz?Δ(1 ? ¦z¦2)¦f′(z)¦(1 + ¦f(z)¦2) ? C1sin(π ? (?2))/ (π ? (g92)), where C1 = limn→∞∥ znand12 < C1 < 2e. Next, U represents the Seidel's class containing all non-constant functions f(z) bounded analytic in Δ such that ¦tf(ei0)¦ = 1 almost everywhere. It is proved that inff?Uf∥ = 0, and if f has either no singularities or only isolated singularities on ?Δ, then ∥f∥ ? C1. Finally, it is proved that if f is a function normal in Δ, namely, the norm ∥f∥< ∞, then we have the sharp estimate ∥fp∥ ? pf∥, for any positive integer p.  相似文献   

15.
Asymptotic results are obtained for pA(k)(n), the kth difference of the function pA(n) which is the number of partitions of n into integers from A. Under certain restrictions on A it is shown that
PA(k+1)(n)PA(k)(n) = O(n?1/2) (n→ ∫)
thereby verifying for these A a conjecture of Bateman and Erdös.  相似文献   

16.
It is proved that Wigner's semicircle law for the distribution of eigenvalues of random matrices, which is important in the statistical theory of energy levels of heavy nuclei, possesses the following completely deterministic version. Let An=(aij), 1?i, ?n, be the nth section of an infinite Hermitian matrix, {λ(n)}1?k?n its eigenvalues, and {uk(n)}1?k?n the corresponding (orthonormalized column) eigenvectors. Let v1n=(an1,an2,?,an,n?1), put
Xn(t)=[n(n-1)]-12k=1[(n-1)t]|vn1uf(n-1)|2,0?t?1
(bookeeping function for the length of the projections of the new row v1n of An onto the eigenvectors of the preceding matrix An?1), and let finally
Fn(x)=n-1(number of λk(n)?xn,1?k?n)
(empirical distribution function of the eigenvalues of Ann. Suppose (i) limnannn=0, (ii) limnXn(t)=Ct(0<C<∞,0?t?1). Then
Fn?W(·,C)(n→∞)
,where W is absolutely continuous with (semicircle) density
w(x,C)=(2Cπ)-1(4C-x212for|x|?2C0for|x|?2C
  相似文献   

17.
For a(1) ? a(2) ? ··· ? a(n) ? 0, b(1) ? b(2) ? ··· ? b(n) ? 0, the ordered values of ai, bi, i = 1, 2,…, n, m fixed, m ? n, and p ? 1 it is shown that
1naibi ? 1map(i)1p1m?k?1 bq(i)+bq[m?k](k+1)qp1q
where 1p + 1q = 1, b[j] = b(j) + b(j + 1) + ··· + b(n), and k is the integer such that b(m ? k ? 1) ? b[m ? k](k + 1) and b(m ? k) < b[m ? k + 1]k. The inequality is shown to be sharp. When p < 1 and a(i)'s are in increasing order then the inequality is reversed.  相似文献   

18.
For an n × n Hermitean matrix A with eigenvalues λ1, …, λn the eigenvalue-distribution is defined by G(x, A) := 1n · number {λi: λi ? x} for all real x. Let An for n = 1, 2, … be an n × n matrix, whose entries aik are for i, k = 1, …, n independent complex random variables on a probability space (Ω, R, p) with the same distribution Fa. Suppose that all moments E | a | k, k = 1, 2, … are finite, Ea=0 and E | a | 2. Let
M(A)=σ=1s θσPσ(A,A1)
with complex numbers θσ and finite products Pσ of factors A and A1 (= Hermitean conjugate) be a function which assigns to each matrix A an Hermitean matrix M(A). The following limit theorem is proved: There exists a distribution function G0(x) = G1x) + G2(x), where G1 is a step function and G2 is absolutely continuous, such that with probability 1 G(x, M(Ann12)) converges to G0(x) as n → ∞ for all continuity points x of G0. The density g of G2 vanishes outside a finite interval. There are only finitely many jumps of G1. Both, G1 and G2, can explicitly be expressed by means of a certain algebraic function f, which is determined by equations, which can easily be derived from the special form of M(A). This result is analogous to Wigner's semicircle theorem for symmetric random matrices (E. P. Wigner, Random matrices in physics, SIAM Review9 (1967), 1–23). The examples ArA1r, Ar + A1r, ArA1r ± A1rAr, r = 1, 2, …, are discussed in more detail. Some inequalities for random matrices are derived. It turns out that with probability 1 the sharpened form
lim supn→∞i=1ni(n)|2?6An62? 0.8228…
of Schur's inequality for the eigenvalues λi(n) of An holds. Consequently random matrices do not tend to be normal matrices for large n.  相似文献   

19.
20.
Families of minimax estimators are found for the location parameters of a p-variate distribution of the form
1(2πσ2)e?(12)6X?θ62dG(σ)
, where G(·) is a known c.d.f. on (0, ∞), p ≥ 3 and the loss is sum of squared errors. The estimators are of the form (1 ? ar(X′X)E0(1X′X)X′X)X where 0 ≤ a ≤ 2, r(XX) is nondecreasing, and r(X′X)X′X is nonincreasing. Generalized Bayes minimax estimators are found for certain G(·)'s.  相似文献   

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