Rick S. Blum

Lehigh University
0000-0002-1024-6771
https://engineering.lehigh.edu/ece/faculty/880
Publications416
h-index52
Citations12,112
Highly Influential Citations607
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Spatial Diversity in Radars—Models and Detection Performance
TLDR
An optimal detector invariant to the signal and noise levels is developed and analyzed for statistical MIMO radar. Expand
A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application
TLDR
A generic image fusion framework based on multiscale decomposition is studied. Expand
Optimized signaling for MIMO interference systems with feedback
TLDR
We propose several numerical approaches to decide the covariance matrices of the transmitted signals and compare their performance in terms of the system mutual information of a multiple-input multiple-output (MIMO) system with multiple users which mutually interfere. Expand
Target Localization Accuracy Gain in MIMO Radar-Based Systems
TLDR
This paper presents an analysis of target localization accuracy, attainable by the use of multiple-input multiple-output (MIMO) radar systems, configured with multiple transmit and receive sensors, widely distributed over an area. Expand
A new automated quality assessment algorithm for image fusion
TLDR
We propose a perceptual quality evaluation method for image fusion which is based on human visual system (HVS) models. Expand
MIMO capacity with interference
  • Rick S. Blum
  • Computer Science
  • IEEE J. Sel. Areas Commun.
  • 11 June 2003
TLDR
We show that the optimum signaling is sometimes different from cases where the users do not interfere with each other and we show how to find the regions where each approach is best. Expand
Energy Efficient Signal Detection in Sensor Networks Using Ordered Transmissions
TLDR
We describe a highly efficient approach which saves transmissions over either the optimum unconstrained energy approach or per-sensor censoring while achieving the same error probability as these approaches. Expand
Multiuser diversity for a dirty paper approach
TLDR
We propose a greedy algorithm based on QR decomposition of the channel and dirty paper precoding to exploit the multiuser diversity of the Gaussian vector broadcast channel. Expand
The good, bad and ugly: distributed detection of a known signal in dependent Gaussian noise
TLDR
Bayes-optimal binary quantization for the detection of a shift in mean in a pair of dependent Gaussian random variables is studied. Expand
Distributed detection with multiple sensors II. Advanced topics
Following the foundational work that established basic ideas for optimum distributed defection schemes using multiple sensors (as reviewed in Part I of this two-part review), further work on… Expand
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