State estimation over packet dropping networks using multiple description coding
Automatica (Journal of IFAC)
Tabu search based multi-watermarks embedding algorithm with multiple description coding
Information Sciences: an International Journal
A three-layer scheme for M-channel multiple description image coding
Signal Processing
Comparison and optimization of packet loss recovery methods based on AMR-WB for VoIP
Speech Communication
Suppressing the Cliff Effect in Video Reproduction Quality
Bell Labs Technical Journal
Joint source-channel coding as an element of a QoS framework for '4G' wireless multimedia
Computer Communications
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Consider a sequence of independent identically distributed (i.i.d.) random variablesX_{l},X_{2}, cdots, X_{n}and a distortion measured(X_{i},X̂_{i})on the estimatesX̂_{i}ofX_{i}. Two descriptionsi(X)in {1,2, cdots ,2^{nR_{1}}andj(X)in {1,2, cdots,2^{nR_{2}}are given of the sequenceX=(X_{1}, X_{2}, cdots ,X_{n}). From these two descriptions, three estimates(i(X)), X2(j(X)), andhat{X}_{O}(i(X),j(X))are formed, with resulting expected distortionsE frac{1/n} sum^{n}_{k=1} d(X_{k}, hat{X}_{mk})=D_{m}, m=0,1,2.We find that the distortion constraintsD_{0}, D_{1}, D_{2}are achievable if there exists a probability mass distributionp(x)p(hat{x}_{1},hat{x}_{2},hat{x}_{0}|x)withEd(X,hat{x}_{m})leq D_{m}such thatR_{1}>I(X;hat{X}_{1}),R_{2}>I(X;hat{X}_{2}),whereI(cdot)denotes Shannon mutual information. These rates are shown to be optimal for deterministic distortion measures.