Noisy Source Vector Quantization Using Kernel Regression
暂无分享,去创建一个
[1] Robert F. Stengel,et al. Smooth function approximation using neural networks , 2005, IEEE Transactions on Neural Networks.
[2] D. Pollard. A Central Limit Theorem for $k$-Means Clustering , 1982 .
[3] Robert M. Gray,et al. The design of joint source and channel trellis waveform coders , 1987, IEEE Trans. Inf. Theory.
[4] S. P. Lloyd,et al. Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.
[5] Tamás Linder,et al. Rates of convergence in the source coding theorem, in empirical quantizer design, and in universal lossy source coding , 1994, IEEE Trans. Inf. Theory.
[6] Peter Craven,et al. Smoothing noisy data with spline functions , 1978 .
[7] David J. Sakrison,et al. Source encoding in the presence of random disturbance (Corresp.) , 1967, IEEE Trans. Inf. Theory.
[8] Robert M. Gray,et al. An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..
[9] T. Berger. Rate-Distortion Theory , 2003 .
[10] Arne Leijon,et al. Vector quantization of LSF parameters with a mixture of dirichlet distributions , 2013, IEEE Transactions on Audio, Speech, and Language Processing.
[11] Benjamin Pfaff,et al. Handbook Of Image And Video Processing , 2016 .
[12] D.M. Mount,et al. An Efficient k-Means Clustering Algorithm: Analysis and Implementation , 2002, IEEE Trans. Pattern Anal. Mach. Intell..
[13] Alexandre B. Tsybakov,et al. Introduction to Nonparametric Estimation , 2008, Springer series in statistics.
[14] Qiang Du,et al. Centroidal Voronoi Tessellations: Applications and Algorithms , 1999, SIAM Rev..
[15] M. Stone,et al. Cross‐Validatory Choice and Assessment of Statistical Predictions , 1976 .
[16] Kevin McClaning and Tom Vito. Radio Receiver Design , 1942, Nature.
[17] NARIMAN FARVARDIN,et al. Optimal quantizer design for noisy channels: An approach to combined source - channel coding , 1987, IEEE Trans. Inf. Theory.
[18] Ender Ayanoglu,et al. On optimal quantization of noisy sources , 1990, IEEE Trans. Inf. Theory.
[19] Ness B. Shroff,et al. Quantization based on a novel sample-adaptive product quantizer (SAPQ) , 1999, IEEE Trans. Inf. Theory.
[20] D. Ruppert. The Elements of Statistical Learning: Data Mining, Inference, and Prediction , 2004 .
[21] Jan Skoglund,et al. Vector quantization based on Gaussian mixture models , 2000, IEEE Trans. Speech Audio Process..
[22] T. Gasser,et al. Locally Adaptive Bandwidth Choice for Kernel Regression Estimators , 1993 .
[23] Nariman Farvardin,et al. On the performance and complexity of channel-optimized vector quantizers , 1991, IEEE Trans. Inf. Theory.
[24] Kevin L. Priddy,et al. Artificial neural networks - an introduction , 2005, Tutorial text series.
[25] G. Takahara,et al. On noisy source vector quantization via a subspace constrained mean shift algorithm , 2012, 2012 26th Biennial Symposium on Communications (QBSC).
[26] Terrence L. Fine,et al. Optimum mean-square quantization of a noisy input (Corresp.) , 1965, IEEE Trans. Inf. Theory.
[27] Deniz Erdogmus,et al. Locally Defined Principal Curves and Surfaces , 2011, J. Mach. Learn. Res..
[28] Hans S. Witsenhausen,et al. Indirect rate distortion problems , 1980, IEEE Trans. Inf. Theory.
[29] Joel Max,et al. Quantizing for minimum distortion , 1960, IRE Trans. Inf. Theory.
[30] Tamás Linder,et al. On the convergence and applications of mean shift type algorithms , 2012, 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).
[31] Robert M. Gray,et al. A unified approach for encoding clean and noisy sources by means of waveform and autoregressive model vector quantization , 1988, IEEE Trans. Inf. Theory.
[32] Masao Kasahara,et al. A construction of vector quantizers for noisy channels , 1984 .
[33] Fady Alajaji,et al. Design of sample adaptive product quantizers for noisy channels , 2005, IEEE Transactions on Communications.
[34] T. Linder. LEARNING-THEORETIC METHODS IN VECTOR QUANTIZATION , 2002 .
[35] Robert M. Gray,et al. Global convergence and empirical consistency of the generalized Lloyd algorithm , 1986, IEEE Trans. Inf. Theory.
[36] Jack K. Wolf,et al. Transmission of noisy information to a noisy receiver with minimum distortion , 1970, IEEE Trans. Inf. Theory.
[37] Tamás Linder,et al. Empirical quantizer design in the presence of source noise or channel noise , 1997, IEEE Trans. Inf. Theory.
[38] Bhaskar D. Rao,et al. PDF optimized parametric vector quantization of speech line spectral frequencies , 2003, IEEE Trans. Speech Audio Process..
[39] Nariman Farvardin,et al. A study of vector quantization for noisy channels , 1990, IEEE Trans. Inf. Theory.
[40] P. Hedelin,et al. Recursive coding of spectrum parameters , 1999, 1999 IEEE Workshop on Speech Coding Proceedings. Model, Coders, and Error Criteria (Cat. No.99EX351).
[41] Tamás Linder,et al. On some convergence properties of the subspace constrained mean shift , 2013, Pattern Recognit..
[42] Qiang Du,et al. Convergence of the Lloyd Algorithm for Computing Centroidal Voronoi Tessellations , 2006, SIAM J. Numer. Anal..
[43] David G. Stork,et al. Pattern classification, 2nd Edition , 2000 .
[44] Wolfgang Härdle,et al. Applied Nonparametric Regression , 1991 .
[45] Matthew P. Wand,et al. Kernel Smoothing , 1995 .
[46] Allen Gersho,et al. Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.
[47] Boris Tsybakov,et al. Information transmission with additional noise , 1962, IRE Trans. Inf. Theory.
[48] Eva Herrmann,et al. Local Bandwidth Choice in Kernel Regression Estimation , 1997 .
[49] Jonas Samuelsson,et al. Bounded support Gaussian mixture modeling of speech spectra , 2003, IEEE Trans. Speech Audio Process..
[50] Heiko Schwarz,et al. Source Coding: Part I of Fundamentals of Source and Video Coding , 2011, Found. Trends Signal Process..