.. Decoding-procedure, 184 3.7.4 Errors and constraints, p.185

R. Ahlswede and I. Csiszàr, Hypothesis testing with communication constraints, IEEE Trans. Inf. Theory, vol.32, issue.4, pp.533-542, 1986.

R. Ahlswede and I. Csiszar, Common randomness in information theory and cryptography?Part I: Secret sharing, IEEE Trans. Inf. Theory, vol.39, issue.4, pp.1121-1132, 1993.

R. Ahlswede and J. Korner, Source coding with side information and a converse for degraded broadcast channels, IEEE Trans. Inf. Theory, vol.21, issue.34, pp.629-637, 1975.

I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, Wireless sensor networks: a survey, Computer Networks, vol.38, issue.4, pp.393-422, 0197.

A. Barron, The strong ergodic theorem for densities: Generalized Shannon? McMillan?Breiman theorem, Ann. Probab, vol.13, issue.4, pp.1292-1303, 1985.

G. Benitz and J. Bucklew, Asymptotically optimal quantizers for detection of i.i.d. data, IEEE Trans. Inf. Theory, vol.35, issue.109, pp.316-325, 1989.

W. Bennett, Spectra of quantized signals, Bell System Technical Journal, vol.27, issue.135, pp.446-472, 1948.

T. Berger and G. Longo, Multiterminal source coding, The information theory approach to communications, pp.170-231, 1977.

T. Berger and J. Gibson, Lossy source coding, IEEE Trans. Inf. Theory, vol.44, issue.6, pp.2693-2723, 1998.
DOI : 10.1109/18.720552

T. Berger, K. Housewright, J. Omura, S. Yung, and J. Wolfowitz, An upper bound on the rate distortion function for source coding with partial side information at the decoder, IEEE Trans. Inf. Theory, vol.25, issue.6, pp.664-666, 1979.

T. Berger and R. Yeung, Multiterminal source encoding with one distortion criterion, IEEE Trans. Inf. Theory, vol.35, issue.2, pp.228-236, 1989.
DOI : 10.1109/18.32119

T. Berger, Z. Zhang, and H. Viswanathan, The CEO problem, IEEE Trans. Inf. Theory, vol.42, issue.231, pp.887-902, 1996.

A. Bhattacharyya, On a measure of divergence between two statistical populations defined by their probability distributions, Bull. Calcutta Math. Soc, vol.35, issue.113, pp.99-109, 1943.

P. Bianchi and J. Jakubowicz, Adaptive learning vector quantization for on-line maximum likelihood estimation Work in progress, pp.233-234, 2011.

P. Billingsley, Probability and Measure, pp.127-219, 1995.

M. Bloch and J. Laneman, On the secrecy capacity of arbitrary wiretap channels, Proc. Allerton, pp.818-825, 2008.

D. Bosq, Nonparametric statistics for stochastic processes: estimation and prediction, p.209, 1998.

R. Bradley, Basic properties of strong mixing conditions. a survey and some open questions, Probab. Surv, vol.2, issue.203, pp.107-144, 2005.

L. Breiman, The individual ergodic theorem of information theory, Ann. Math. Stat, vol.28, issue.3, pp.809-811, 1957.

F. Bullo, J. Cortés, and S. Martinez, Distributed control of robotic networks, pp.28-132, 2009.

O. Cappé, E. Moulines, and T. Ryden, Inference in Hidden Markov Models. Springer series in statistics, pp.219-235, 2007.

J. Chamberland and V. Veeravalli, How dense should a sensor network be for detection with correlated observations?, IEEE Trans. Inf. Theory, vol.52, issue.11, pp.5099-5106, 0199.

B. Chen, L. Tong, and P. Varshney, Channel-aware distributed detection in wireless sensor networks, IEEE Signal Process. Mag, vol.1053, issue.588806, pp.16-26, 0197.

J. Chen and T. Berger, Successive Wyner?Ziv coding scheme and its application to the quadratic Gaussian CEO problem, IEEE Trans. Inf. Theory, vol.54, issue.4, pp.1586-1603, 2008.

P. Chen, General formulas for the Neyman?Pearson type-II error exponent subject to fixed and exponential type-I error bounds Wiretap channel with side information, IEEE Trans. Inf. Theory IEEE Trans. Inf. Theory, vol.42, issue.138, pp.316-323, 1996.

J. Conway and N. Sloane, Sphere packings, lattices, and groups, pp.95-212, 1999.

M. Costa, Writing on dirty paper, IEEE Trans. Inf. Theory, vol.29, issue.3, pp.439-441, 0191.

T. Cover and J. Thomas, Elements of information theory Wiley-Interscience, pp.189-272, 0198.

I. Csiszár and J. Körner, Broadcast channels with confidential messages, IEEE Trans. Inf. Theory, vol.24, issue.170, pp.339-348, 0194.

I. Csiszar and J. Korner, Towards a general theory of source networks, IEEE Trans. Inf. Theory, vol.26, issue.2, pp.155-165, 1980.

I. Csiszar and J. Körner, Information theory: coding theorems for discrete memoryless systems, Akadémiai Kiado, vol.26, issue.28, pp.130-132, 1982.

A. Detti and N. Blefari-melazzi, Network layer solutions for a content-centric internet, Trustworthy Internet, pp.359-369, 2011.

R. Douc, E. Moulines, and T. Ryden, Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime, Ann. Stat, vol.32, issue.102, pp.2254-2304, 2004.

P. Doukhan, Mixing: properties and examples, 1994.

E. Ekrem and S. Ulukus, The secrecy capacity region of the Gaussian MIMO multireceiver wiretap channel, IEEE Trans. Inf. Theory, vol.57, issue.4, pp.2083-2114, 2011.

A. Gamal and Y. Kim, Lecture Notes on Network Information Theory, pp.244-248

T. Flynn and R. Gray, Encoding of correlated observations, IEEE Trans. Inf. Theory, vol.33, issue.112, pp.773-787, 1987.

N. Freris, H. Kowshik, and P. Kumar, Fundamentals of large sensor networks: Connectivity, capacity, clocks, and computation, Proc. IEEE, pp.1828-1846, 2010.

Y. Gao and E. Tuncel, New hybrid digital/analog schemes for transmission of a Gaussian source over a Gaussian channel, IEEE Trans. Inf. Theory, vol.56, issue.12, pp.6014-6019, 2010.

E. Gassiat and S. Boucheron, Optimal error exponents in hidden Markov models order estimation, IEEE Trans. Inf. Theory, vol.49, issue.113, pp.964-980, 2003.

M. Gastpar, B. Rimoldi, and M. Vetterli, To code, or not to code: lossy sourcechannel communication revisited, IEEE Trans. Inf. Theory, vol.49, issue.80, pp.1147-1158, 0193.

S. Gel-'fand and M. Pinsker, Coding for channel with random parameters, Probl. Control Inf. Theory, vol.9, issue.72, pp.19-31, 1980.

A. Gersho, Asymptotically optimal block quantization, IEEE Trans. Inf. Theory, vol.25, issue.4, pp.373-380, 1979.
DOI : 10.1109/tit.1979.1056067

A. Gersho and R. Gray, Vector quantization and signal compression. Kluwer, pp.198-210, 1992.
DOI : 10.1007/978-1-4615-3626-0

V. Girardin, On the different extensions of the ergodic theorem of information theory, pp.163-179, 2005.

J. Goblick and T. , Theoretical limitations on the transmission of data from analog sources, IEEE Trans. Inf. Theory, vol.11, issue.4, pp.558-567, 0193.

S. Graf and H. Luschgy, Foundations of quantization for probability distributions, pp.129-228, 2000.

R. Gray and D. Neuhoff, Quantization, IEEE Trans. Inf. Theory, vol.44, issue.129, pp.2325-2383, 1998.

D. Gündüz, E. Erkip, and H. Poor, Lossless compression with security constraints, Proc. ISIT, pp.111-115, 2008.

D. Gündüz, J. Nayak, and E. Tuncel, Wyner-Ziv coding over broadcast channels using hybrid digital/analog transmission, Proc. ISIT, pp.58-166, 2008.

D. Guo, S. Shamai, and S. Verdu, Mutual information and minimum mean-square error in Gaussian channels, IEEE Trans. Inf. Theory, vol.51, issue.4, pp.1261-1282, 2005.

R. Gupta, Quantization strategies for low-power communications, p.212, 2001.

R. Gupta and A. Hero, High-rate vector quantization for detection, IEEE Trans. Inf. Theory, vol.49, issue.135, pp.1951-1969, 2003.

W. Hachem, E. Moulines, and F. Roueff, Error exponents for Neyman-Pearson detection of a continuous-time Gaussian Markov process from regular or irregular samples, IEEE Trans. Inf. Theory, vol.57, issue.101, pp.3899-3914, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00604392

T. Han and K. Kobayashi, A unified achievable rate region for a general class of multiterminal source coding systems, IEEE Trans. Inf. Theory, vol.26, issue.3, pp.277-288, 1980.

T. Han and S. Amari, Statistical inference under multiterminal data compression, IEEE Trans. Inf. Theory, vol.44, issue.84, pp.2300-2324, 0198.

M. Hayashi and R. Matsumoto, Construction of wiretap codes from ordinary channel codes, Proc. ISIT, pp.2538-2542, 2010.

C. Heegard and T. Berger, Rate distortion when side information may be absent, IEEE Trans. Inf. Theory, vol.31, issue.6, pp.727-734, 1985.
DOI : 10.1109/tit.1985.1057103

W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, An application-specific protocol architecture for wireless microsensor networks, IEEE Trans. Wireless Commun, vol.1, issue.4, pp.660-670, 2002.

S. Jana and R. Blahut, Partial side information problem: Equivalence of two inner bounds, Proc. CISS, pp.1005-1009, 2008.

A. Kaspi and T. Berger, Rate-distortion for correlated sources with partially separated encoders, IEEE Trans. Inf. Theory, vol.28, issue.6, pp.828-840, 1982.

A. Kaspi, Rate-distortion function when side-information may be present at the decoder, IEEE Trans. Inf. Theory, vol.40, issue.6, pp.2031-2034, 1994.

S. Kassam, Optimum quantization for signal detection, IEEE Trans. Commun, vol.25, issue.84, pp.479-484, 0198.

S. Kay, Fundamentals of statistical signal processing, vol. I Estimation Theory, pp.113-233, 1993.

K. Kittichokechai, T. J. Oechtering, and M. Skoglund, Secure source coding with action-dependent side information, Proc. ISIT, pp.112-230, 2011.
DOI : 10.1109/isit.2011.6033831

A. Kolmogorov, Foundations of the theory of probability, p.127, 1956.

G. Kramer, Capacity results for the discrete memoryless network, IEEE Trans. Inf. Theory, vol.49, issue.1, pp.4-21, 2003.

S. Kullback, Information theory and statistics, pp.31-135, 1978.

H. Kushner and G. Yin, Stochastic approximation and recursive algorithms and applications, p.234, 2003.

S. Lang, Calculus of several variables, p.293, 1973.

A. Lapidoth and S. Tinguely, Sending a bivariate Gaussian over a Gaussian MAC, IEEE Trans. Inf. Theory, vol.56, issue.6, pp.2714-2752, 2010.

J. Lasserre, A trace inequality for matrix product Casella, Theory of point estimation, IEEE Trans. Autom. Control, vol.40, issue.127, pp.1500-1501, 1995.

E. Lehmann and J. Romano, Testing Statistical Hypotheses, 0198.

Y. Liang, H. Poor, and S. Shamai, Secure communication over fading channels, IEEE Trans. Inf. Theory, vol.54, issue.138, pp.2470-2492, 2008.

S. H. Lim, P. Minero, and Y. Kim, Lossy communication of correlated sources over multiple access channels, Proc. Allerton, pp.166-184, 2010.

P. Lima and L. Custdio, Multi-Robot Systems, ser. Studies in Computational Intelligence, pp.1-64, 2005.

Y. Linde, A. Buzo, and R. Gray, An algorithm for vector quantizer design, IEEE Trans. Commun, vol.28, issue.1, pp.84-95, 1980.

J. Liu, Monte Carlo strategies in scientific computing, pp.105-223, 2001.

R. Liu, Y. Liang, H. Poor, and P. Spasojevic, Secure nested codes for type II wiretap channels, Proc. ITW, pp.337-342, 2007.

T. Liu and P. Viswanath, An extremal inequality motivated by multiterminal information-theoretic problems, IEEE Trans. Inf. Theory, vol.53, issue.5, pp.1839-1851, 2007.

A. Liveris, Z. Xiong, and C. Georghiades, Compression of binary sources with side information at the decoder using LDPC codes, IEEE Commun. Lett, vol.6, issue.10, pp.440-442, 2002.

S. Lloyd, Least squares quantization in PCM, IEEE Trans. Inf. Theory, vol.28, issue.26, pp.129-137, 1982.

A. Lozano, A. Tulino, and S. Verdu, Optimum power allocation for parallel Gaussian channels with arbitrary input distributions, IEEE Trans. Inf. Theory, vol.52, issue.7, pp.3033-3051, 2006.

H. Mahdavifar and A. Vardy, Achieving the secrecy capacity of wiretap channels using polar codes, Proc. ISIT, pp.913-917, 2010.

A. Marshall and I. Olkin, Inequalities: theory of majorization and its applications, p.213, 1979.

U. Maurer, Secret key agreement by public discussion from common information, IEEE Trans. Inf. Theory, vol.39, issue.3, pp.733-742, 1993.
DOI : 10.1109/18.256484
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.45.5984

B. Mcmillan, The basic theorems of information theory, Ann. Math. Stat, vol.24, issue.2, pp.196-219, 1953.

N. Merhav, On the Shannon cipher system with a capacity-limited keydistribution channel, IEEE Trans. Inf. Theory, vol.52, issue.3, pp.1269-1273, 2006.

N. Merhav and S. Shamai, On joint source-channel coding for the Wyner-Ziv source and the Gel'fand-Pinsker channel, IEEE Trans. Inf. Theory, vol.49, issue.11, pp.2844-2855, 2003.

V. Misra, V. K. Goyal, and L. R. Varshney, Distributed scalar quantization for computing: High-resolution analysis and extensions, IEEE Trans. Inf. Theory, vol.57, issue.84, pp.5298-5325, 0198.

U. Mittal and N. Phamdo, Hybrid digital-analog (HDA) joint source-channel codes for broadcasting and robust communications, IEEE Trans. Inf. Theory, vol.48, issue.5, pp.1082-1102, 2002.

S. Moy, Generalizations of Shannon?McMillan theorem, Pacific J. Math, vol.11, issue.203, pp.705-714, 1961.

S. Na and D. Neuhoff, Bennett's integral for vector quantizers, IEEE Trans. Inf. Theory, vol.41, issue.85, pp.886-900, 1995.

C. Nair, Capacity regions of two new classes of 2-receiver broadcast channels, Proc. ISIT, pp.1839-1843, 2009.

A. Narayanan and V. Shmatikov, Capacity regions of two new classes of two-receiver broadcast channels Robust de-anonymization of large sparse datasets, IEEE Symposium on Security and Privacy, pp.4207-4214, 2008.

D. Neuhoff, On the asymptotic distribution of the errors in vector quantization, IEEE Trans. Inf. Theory, vol.42, issue.2, pp.461-468, 1996.

F. Oggier, P. Solé, and J. Belfiore, Lattice codes for the wiretap Gaussian channel: Construction and analysis, arXiv cs.IT, arXiv:1103.4086v1, pp.1-40, 2011.

B. Oliver, J. Pierce, and C. Shannon, The philosophy of PCM, Proc. IRE, pp.1324-1331, 1948.

Y. Oohama, Gaussian multiterminal source coding, IEEE Trans. Inf. Theory, vol.43, issue.55, pp.1912-1923, 1997.
DOI : 10.1109/isit.1995.535776

P. Panter and W. Dite, Quantization distortion in pulse-count modulation with nonuniform spacing of levels, Proc. IRE, pp.44-48, 1951.

J. Pearl, Fusion, propagation, and structuring in belief networks, Artificial intelligence, vol.29, issue.3, pp.241-288, 1986.

F. Perez-cruz, M. Rodrigues, and S. Verdu, MIMO Gaussian channels with arbitrary inputs: Optimal precoding and power allocation, IEEE Trans. Inf. Theory, vol.56, issue.3, pp.1070-1084
DOI : 10.1109/tit.2009.2039045
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.207.719

K. Perlmutter, S. Perlmutter, R. Gray, R. Olshen, and K. Oehler, Bayes risk weighted vector quantization with posterior estimation for image compression and classification, IEEE Trans. Image Process, vol.5, issue.84, pp.347-360, 0198.

H. Permuter and T. Weissman, Source coding with a side information " vending machine, IEEE Trans. Inf. Theory, vol.57, issue.112, pp.4530-4544, 2011.

H. Permuter, Y. Steinberg, and T. Weissman, Two-way source coding with a helper, IEEE Trans. Inf. Theory, vol.56, issue.6, pp.2905-2919, 2010.

B. Picinbono and P. Duvaut, Optimum quantization for detection, IEEE Trans. Commun, vol.36, issue.84, pp.1254-1258, 0198.

H. Poor, Fine quantization in signal detection and estimation, IEEE Trans. Inf. Theory, vol.34, issue.113, pp.960-972, 0198.

H. Poor and J. Thomas, Applications of Ali?Silvey distance measures in the design of generalized quantizers for binary decision systems, IEEE Trans. Commun, vol.25, issue.84, pp.893-900, 0198.

V. Prabhakaran and K. Ramchandran, On secure distributed source coding, Proc. ITW, pp.442-447, 2007.

S. Pradhan and K. Ramchandran, Distributed source coding using syndromes (DISCUS): design and construction, IEEE Trans. Inf. Theory, vol.49, issue.3, pp.626-643, 2003.
DOI : 10.1109/dcc.1999.755665
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.27.7164

M. Rahman and A. Wagner, Rate region of the Gaussian scalar-help-vector sourcecoding problem, Proc. ISIT, pp.56-60, 2010.

C. Rasmussen and C. Williams, Gaussian processes for machine learning, p.282, 2006.

L. Sankar, S. Rajagopalan, and H. Poor, A theory of privacy and utility in databases, arXiv cs.IT, vol.113, pp.1-35, 2011.

S. Servetto, Lattice quantization with side information: Codes, asymptotics, and applications in sensor networks, IEEE Trans. Inf. Theory, vol.53, issue.2, pp.714-731, 2007.

C. Shannon, A mathematical theory of communication, Bell System Technical Journal, vol.27, issue.130, pp.379-423, 1948.

M. Skolnik143, ]. Slepian, and J. Wolf, Radar handbook Noiseless coding of correlated information sources, IEEE Trans. Inf. Theory, vol.23, issue.157, pp.471-480, 1973.

Y. Sung, L. Tong, and H. Poor, Neyman?Pearson detection of Gauss?Markov signals in noise : closed-form error exponent and properties, IEEE Trans. Inf. Theory, vol.52, issue.101, pp.1354-1365, 2006.

Y. Sung, S. Misra, L. Tong, and A. Ephremides, Signal processing for applicationspecific ad hoc networks, IEEE Signal Process. Mag, vol.23, issue.5, pp.74-83, 2006.

R. Tandon, S. Ulukus, and K. Ramchandran, Secure source coding with a helper, Proc. Allerton, pp.1061-1068, 2009.

S. Tavildar, P. Viswanath, and A. Wagner, The Gaussian many-help-one distributed source coding problem, IEEE Trans. Inf. Theory, vol.56, issue.138, pp.564-581, 2010.

R. Tenney and N. Sandell, Detection with distributed sensors, IEEE Trans. Aerosp. Electron. Syst, vol.17, issue.84, pp.501-510, 0198.

C. Tian and S. Diggavi, On multistage successive refinement for Wyner?Ziv source coding with degraded side informations, IEEE Trans. Inf. Theory, vol.53, issue.8, pp.2946-2960, 2007.

R. Timo, T. Chan, and A. Grant, Rate distortion with side-information at many decoders, IEEE Trans. Inf. Theory, vol.57, issue.138, pp.5240-5257, 2011.

J. Tsitsiklis, Decentralized detection by a large number of sensors, Math. Control Signals Systems, vol.1, issue.84, pp.167-182, 0198.

J. Villard, FMG, a basic Matlab GUI for Fourier-Motzkin elimination Available: http://www.joffrey-villard, pp.74-144, 2011.

A. Wagner, B. Kelly, and Y. Altug, The lossy one-helper conjecture is false, Proc. Allerton, pp.716-723, 2009.

A. Wagner, S. Tavildar, and P. Viswanath, Rate region of the quadratic Gaussian two-encoder source-coding problem, IEEE Trans. Inf. Theory, vol.54, issue.138, pp.1938-1961, 2008.

P. Walters, An introduction to ergodic theory, p.127, 1982.

P. Willett, P. Swaszek, and R. Blum, The good, bad, and ugly: Distributed detection of a known signal in dependent Gaussian noise, IEEE Trans. Signal Process, vol.48, issue.12, pp.3266-3279, 0199.

M. Wilson, K. Narayanan, and G. Caire, Joint source channel coding with side information using hybrid digital analog codes, IEEE Trans. Inf. Theory, vol.56, issue.81, pp.4922-4940, 2010.

J. Wolfowitz, Coding Theorems of Information Theory, p.129, 1964.

A. Wyner, On source coding with side information at the decoder, IEEE Trans. Inf. Theory, vol.21, issue.35, pp.294-300, 1975.

A. Wyner and J. Ziv, A theorem on the entropy of certain binary sequences and applications?Part I, IEEE Trans. Inf. Theory, vol.19, issue.6, pp.769-772, 1973.

A. Wyner, The wire-tap channel, Bell System Technical Journal, vol.54, issue.131, pp.1355-1387, 1975.
DOI : 10.1002/j.1538-7305.1975.tb02040.x

A. Wyner and J. Ziv, The rate-distortion function for source coding with side information at the decoder, IEEE Trans. Inf. Theory, vol.22, issue.139, pp.1-10, 1976.

J. Xiao, A. Ribeiro, Z. Luo, and G. Giannakis, Distributed compressionestimation using wireless sensor networks, IEEE Signal Process. Mag, vol.23, issue.84, pp.27-41, 0198.

E. Yair, K. Zeger, and A. Gersho, Competitive learning and soft competition for vector quantizer design A source coding problem for sources with additional outputs to keep secret from the receiver or wiretappers, IEEE Trans. Signal Process. IEEE Trans. Inf. Theory, vol.40, issue.35, pp.294-309, 1983.

R. Zamir and M. Feder, On lattice quantization noise, IEEE Trans. Inf. Theory, vol.42, issue.4, pp.1152-1159, 1996.

R. Zamir, S. Shamai, and U. Erez, Nested linear/lattice codes for structured multiterminal binning, IEEE Trans. Inf. Theory, vol.48, issue.6, pp.1250-1276, 2002.