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Binary data

Known as: Binary variable, Binary random variable, Dichotomized response variable 
Binary data is data whose unit can take on only two possible states, traditionally termed 0 and +1 in accordance with the binary numeral system and… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2012
2012
Multiantenna GLR Detection of Rank-One Signals With Known Power Spectrum in White Noise With Unknown Spatial Correlation
Multiple-antenna detection of a Gaussian signal with spatial rank one in temporally white Gaussian noise with arbitrary and… 
Highly Cited
2010
Highly Cited
2010
Dimensioning and worst-case analysis of cluster-tree sensor networks
Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their… 
Highly Cited
2007
Highly Cited
2007
Opportunistic Feedback for Multiuser MIMO Systems With Linear Receivers
A novel multiuser scheduling and feedback strategy for the multiple-input multiple-output (MIMO) downlink is proposed in this… 
2007
2007
Tree-net architecture for integrated all-optical arithmetic operations and data comparison scheme with optical nonlinear material
2006
2006
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous… 
2006
2006
Regular Minimality: A Fundamental Law of Discrimination.
The term discrimination in this chapter is understood in the meaning of telling stimuli apart. More specifically, it refers to a… 
2005
2005
Matching with Multiple Control Groups , and Adjusting for Group Differences
When estimating causal effects from observational data, it is desirable to replicate a randomized experiment as closely as… 
1999
1999
Group contribution methods–ideal tools for the synthesis and design of separation processes
Abstract 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
Highly Cited
1991
Highly Cited
1991
Optimum and heuristic algorithms for an approach to finite state machine decomposition
Optimum and heuristic algorithms for the general decomposition of finite state machines (FSMs) such that the sum total of the… 
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