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The classical textbooks on speech coding are Jayant and Noll [1984] and Kleijn and Paliwal [1995], which, at the time of this writing, are unfortunately out of print. The excellent textbook by Vary et al. [1998] is written in German, but an improved edition in English is in preparation. Recently, a second edition of Kondoz [2004] has appeared. Another excellent overview of various aspects of speech processing is Rabiner [1994]. Source-coding theory is treated in Berger [1971], Gray [1989], and Kleijn [2005] which is maybe best suited for the needs of speech coding. For speech signal processing in general, we recommend the classic Rabiner and Schafer [1978] and the more recent textbooks of Deller et al. [2000], O Shaughnessy [2000], and Quatieri [2002]. For extensions to nonlinear speech modeling, see Chollet et al. [2005] and Kubin [1995]. In Gersho and Gray [1992] an extensive discussion of VQ is provided. Hanzo et al. [2001] address joint solutions for source and channel coding for wireless speech transmission. The wider context of acoustic signal processing for telecommunications is treated in Gay and Benesty [2000], Haensler and Schmidt [2004], and Vaseghi [2000]. Bandwidth extension is the main topic of Larsen and Aarts [2004]. An excellent reference for spoken language processing is Huang et al. [2001] and Jurafsky and Martin [2000]. Gibson et al. [1998] treat the compression of general multimedia data. For updates and errata for this chapter, see wides.usc.edu/teaching/textbook

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Crystal orientation varies around channel (narrow beam) Interface states and VT smearing Source/drain fanout difficult to fabricate Small current carrying capacity per channel; inflexible VT control; enhanced quantum effects (narrow beam) VT very sensitive to beam width; difficult doping profile control; wider structures have poorer scaling properties (wide beam) P/N junction turnon limits gate voltage High resistance of body gate

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he Hole Wizard and Toolbox are two applications that go together because of the information they share; they both work from a single database of matching hole and screw sizes. One of the most useful examples of combining these two applications is the ability to automatically place holes through multiple parts and put appropriately sized screws and hardware into the holes, all in one step. The hole knows which fastener or stack of fasteners needs to go together.

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respectively. nor We note that (lO.l), followed by (10.5), does not in general restore P; does (10.3, followed by (10.l), restore (E,, E*).But, from the second round on, matters stabilize. We say that P and ( E ,, E') represent each other if they mutually induce each other through (10.1) and (10.5). Similarly, we say that P and (v,. v") represent each other if they mutually induce each other through (10.2) and (10.6). Obviously, it suffices to look at one member of the respective pairs ( E ,. E " ) and (w*, * ) , say E* and w*. u These notions immediately provoke a few questions: (1) What conditions must ( E ,, E * ) satisfy so that it is representable by some P What conditions must P satisfy so that it is representable by some ( E , , E*) (2) What conditions must (w*,v*) satisfy so that it is representable by some P What conditions must P satisfy so that it is representable by some (w*,v*) The answer to (1) is very simple. We first note that every representable P is closed and convex (since we are working with finite sets 0, P can be identified with a subset of the simplex { ( p l , . . . . p n ) I C p , = 1.p , 2 0}, so there is a unique natural topology). On the other hand every representable E* is monotone,

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for 0 5 d 5 do < m. Thus assumptions (N-3) (ii) and (iii) are satisfied, provided that E (1 2 5K <c c (6.22) in some neighborhood of 60.This certainly holds if the true underlying distribution has a density with respect to Lebesgue measure. Furthermore, under the same condition (6.22), we have

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