1 The eigenvalue distribution function For an N × N matrix AN , the eigenvalue distribution function 1 (e.d.f.) F AN (x) is defined as F AN (x) = Number of eigenvalues of AN ≤ x . (1) N As defined, the e.d.f. is right continuous and possibly atomic i.e. with step discontinuities at discrete points. In practical terms, the derivative of (1), referred to as the (eigenvalue) level density, is simply the
chapter 9 GRAPH ALGORITHMs $I Definitions e G(V,E) where G: =graph, V=V(G): :=finite nonempty set of vertices, andE=E(G): : = finite set of edges. d' Undirected graph:(V;,vi)=(j,vi): =the same edge 6 Directed graph(digraph): :=2* I tailhead
3.1 A brief history of western E.P. The foundation of E.P.: before 1920s Wundt,1879: methodology James, “Talks to the teachers” 1899; “The principles of psychology”1890; Dewey: apply psychology to education
Theory of Equivalence Relations (A, R) (E1) For all x : xRx. (E2) For all x, y : If xRy then yRx. (E3) For all x, y, z : If xRy and yRz then xRz. Logic in Computer Science – p.2/16
I.Choose the Correct Answer 1. A disturbance can be written x b xt b t a y(x,t) (e e e ) 2 2 −( / ) 2 / − = . This disturbance is ( D ) (A) Not a traveling wave. (B) A traveling wave with speed v = a. (C) A traveling wave with speed v = a/b. (D) A traveling wave with speed v = b