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» Stratified random sampling for power estimation
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IPSN
2004
Springer
15 years 3 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
BMCBI
2004
90views more  BMCBI 2004»
14 years 9 months ago
Statistical monitoring of weak spots for improvement of normalization and ratio estimates in microarrays
Background: Several aspects of microarray data analysis are dependent on identification of genes expressed at or near the limits of detection. For example, regression-based normal...
Igor Dozmorov, Nicholas Knowlton, Yuhong Tang, Mic...
BMCBI
2008
108views more  BMCBI 2008»
14 years 9 months ago
A nonparametric model for quality control of database search results in shotgun proteomics
Background: Analysis of complex samples with tandem mass spectrometry (MS/MS) has become routine in proteomic research. However, validation of database search results creates a bo...
Jiyang Zhang, Jianqi Li, Xin Liu, Hongwei Xie, Yun...
CSDA
2007
151views more  CSDA 2007»
14 years 9 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
90
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GLOBECOM
2010
IEEE
14 years 7 months ago
Automatic Gain Control for ADC-Limited Communication
As the date rates and bandwidths of communication systems scale up, the cost and power consumption of highprecision (e.g., 8-12 bits) analog-to-digital converters (ADCs) become pro...
Feifei Sun, Jaspreet Singh, Upamanyu Madhow