SPTM-P3: Adaptive and Nonlinear Signal Processing |
| Session Type: Poster |
| Time: Tuesday, May 28, 15:30 - 17:30 |
| Location: Poster Area I |
| Session Chair: Steve McLaughlin, Heriot Watt Universit
|
| |
|
SPTM-P3.1: KALMAN-LIKE STATE TRACKING AND CONTROL IN POMDPS WITH APPLICATIONS TO BODY SENSING NETWORKS |
| Daphney-Stavroula Zois; University of Southern California |
| Marco Levorato; University of Southern California |
| Urbashi Mitra; University of Southern California |
| |
|
SPTM-P3.2: ADAPTIVE SPECTRUM SENSING AND ESTIMATION |
| Dennis Wei; University of Michigan |
| Alfred Hero; University of Michigan |
| |
|
SPTM-P3.3: LINEARLY RECONFIGURABLE KALMAN FILTERING FOR A VECTOR PROCESS |
| Feng Jiang; University of California, Irvine |
| Jie Chen; University of California, Irvine |
| A. Lee Swindlehurst; University of California, Irvine |
| |
|
SPTM-P3.4: THE GENERALIZED SLIDING-WINDOW RECURSIVE LEAST-SQUARES LATTICE FILTER |
| Hugo M. Spinelli; Universidade Federal do Rio de Janeiro |
| Ricardo Merched; Universidade Federal do Rio de Janeiro |
| |
|
SPTM-P3.5: KERNEL LMS ALGORITHM WITH FORWARD-BACKWARD SPLITTING FOR DICTIONARY LEARNING |
| Wei Gao; Université de Nice-Sophia Antipolis |
| Jie Chen; University of Nice Sophia-Antipolis |
| Cédric Richard; Université de Nice-Sophia Antipolis |
| Jianguo Huang; Northwestern Polytechnical University |
| Rémi Flamary; Université de Nice-Sophia Antipolis |
| |
|
SPTM-P3.6: SPARSE VOLTERRA SYSTEMS: THEORY AND PRACTICE |
| Andrew Bolstad; Massachusetts Institute of Technology, Lincoln Laboratory |
| Benjamin Miller; Massachusetts Institute of Technology, Lincoln Laboratory |
| |
|
SPTM-P3.7: EVALUATING THE POTENTIAL OF VOLTERRA-PARAFAC IIR MODELS |
| Phillip Mark Seymour Burt; University of São Paulo |
| José Henrique de Morais Goulart; University of São Paulo |
| |
|
SPTM-P3.8: PARSIMONIOUS MULTIVARIATE COPULA MODEL FOR DENSITY ESTIMATION |
| Alireza Bayestehtashk; Oregon Health & Science University |
| Izhak Shafran; Oregon Health & Science University |
| |
|
SPTM-P3.9: BAYESIAN NONPARAMETRIC STATE AND IMPULSIVE MEASUREMENT NOISE DENSITY ESTIMATION IN NONLINEAR DYNAMIC SYSTEMS |
| Nouha Jaoua; Ecole Centrale de Lille |
| Emmanuel Duflos; Ecole Centrale de Lille |
| Philippe Vanheeghe; Ecole Centrale de Lille |
| François Septier; Telecom Lille 1 |
| |
|
SPTM-P3.10: A SIMPLE OPTIMUM NONLINEAR FILTER FOR STOCHASTIC-RESONANCE-BASED SIGNAL DETECTION |
| Yukihiro Tadokoro; Toyota Central R&D Lab., Inc. |
| Akihisa Ichiki; Toyota Central R&D Lab., Inc. |
| |
|
SPTM-P3.11: POWER ALLOCATION FOR GAUSSIAN MIXTURE MODEL PRIOR KNOWLEDGE IN WIRLESS SENSOR NETWORKS |
| Zeeshan Azmat; University of Technology, Sydney |
| Hoang Tuan; University of Technology, Sydney |
| |
|
SPTM-P3.12: A STUDENT'S T FILTER FOR HEAVY TAILED PROCESS AND MEASUREMENT NOISE |
| Michael Roth; Linköping University |
| Emre Ozkan; Linköping University |
| Fredrik Gustafsson; Linköping University |
| |
|
SPTM-P3.13: NON-PARAMETRIC DATA PREDISTORTION FOR NON-LINEAR CHANNELS WITH MEMORY |
| Roberto Piazza; University of Luxembourg |
| Bhavani Shankar Mysore Rama Rao; University of Luxembourg |
| Bjӧrn Ottersten; University of Luxembourg |
| |
|
SPTM-P3.14: INTRODUCING THE FAST NONLINEAR FOURIER TRANSFORM |
| Sander Wahls; Princeton University |
| H. Vincent Poor; Princeton University |
| |
