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Analyzing the SignaltoNoise Ratio of Direct Sampling Receivers
"... Abstract—The increasing demand for multimode multiband operation in mobile communications requires flexible radio frontends. Direct sampling receivers are very promising for this purpose. For this class of receivers, a proper parameterization of the analogtodigital converter, in terms of input b ..."
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bandwidth, sampling frequency, and quantization resolution, is essential for its operation. This paper evaluates prospects and challenges of direct sampling receivers analytically. The impact of the sampling frequency and the quantization resolution on the signaltonoise ratio of the received bandpass
Receiverdriven Layered Multicast
, 1996
"... State of the art, realtime, rateadaptive, multimedia applications adjust their transmission rate to match the available network capacity. Unfortunately, this sourcebased rateadaptation performs poorly in a heterogeneous multicast environment because there is no single target rate — the conflicti ..."
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Cited by 749 (22 self)
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with a layered transmission system. By selectively forwarding subsets of layers at constrained network links, each user receives the best quality signal that the network can deliver. We and others have proposed that selectiveforwarding be carried out using multiple IPMulticast groups where each
Compressive sampling
, 2006
"... Conventional wisdom and common practice in acquisition and reconstruction of images from frequency data follow the basic principle of the Nyquist density sampling theory. This principle states that to reconstruct an image, the number of Fourier samples we need to acquire must match the desired res ..."
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Cited by 1427 (15 self)
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resolution of the image, i.e. the number of pixels in the image. This paper surveys an emerging theory which goes by the name of “compressive sampling” or “compressed sensing,” and which says that this conventional wisdom is inaccurate. Perhaps surprisingly, it is possible to reconstruct images or signals
Just Relax: Convex Programming Methods for Identifying Sparse Signals in Noise
, 2006
"... This paper studies a difficult and fundamental problem that arises throughout electrical engineering, applied mathematics, and statistics. Suppose that one forms a short linear combination of elementary signals drawn from a large, fixed collection. Given an observation of the linear combination that ..."
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Cited by 496 (2 self)
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that has been contaminated with additive noise, the goal is to identify which elementary signals participated and to approximate their coefficients. Although many algorithms have been proposed, there is little theory which guarantees that these algorithms can accurately and efficiently solve the problem
Directed Diffusion for Wireless Sensor Networking
 IEEE/ACM Transactions on Networking
, 2003
"... Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such ..."
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Cited by 658 (9 self)
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Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm
New Directions in Cryptography
, 1976
"... Two kinds of contemporary developments in cryptography are examined. Widening applications of teleprocessing have given rise to a need for new types of cryptographic systems, which minimize the need for secure key distribution channels and supply the equivalent of a written signature. This paper sug ..."
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Cited by 3499 (7 self)
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Two kinds of contemporary developments in cryptography are examined. Widening applications of teleprocessing have given rise to a need for new types of cryptographic systems, which minimize the need for secure key distribution channels and supply the equivalent of a written signature. This paper suggests ways to solve these currently open problems. It also discusses how the theories of communication and computation are beginning to provide the tools to solve cryptographic problems of long standing.
SIGNALTONOISE RATIOS By
, 2015
"... Consider the following three important problems in statistical inference, namely, constructing confidence intervals for (1) the error of a highdimensional (p> n) regression estimator, (2) the linear regression noise level, and (3) the genetic signaltonoise ratio of a continuousvalued trait (r ..."
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and find that the method applies in practice and in finite samples much more widely than in the regime covered by the theory. Finally, we apply EigenPrism to a genetic dataset to estimate the genetic signaltonoise ratio for a number of continuous phenotypes.
Exact Sampling with Coupled Markov Chains and Applications to Statistical Mechanics
, 1996
"... For many applications it is useful to sample from a finite set of objects in accordance with some particular distribution. One approach is to run an ergodic (i.e., irreducible aperiodic) Markov chain whose stationary distribution is the desired distribution on this set; after the Markov chain has ..."
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Cited by 548 (13 self)
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For many applications it is useful to sample from a finite set of objects in accordance with some particular distribution. One approach is to run an ergodic (i.e., irreducible aperiodic) Markov chain whose stationary distribution is the desired distribution on this set; after the Markov chain
SMOTE: Synthetic Minority Oversampling Technique
 Journal of Artificial Intelligence Research
, 2002
"... An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often realworld data sets are predominately composed of ``normal'' examples with only a small percentag ..."
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Cited by 614 (28 self)
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the majority class. This paper also shows that a combination of our method of oversampling the minority class and undersampling the majority class can achieve better classifier performance (in ROC space) than varying the loss ratios in Ripper or class priors in Naive Bayes. Our method of oversampling
DART: Directed automated random testing
 In Programming Language Design and Implementation (PLDI
, 2005
"... We present a new tool, named DART, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static sourcecode parsing; (2) automatic generation of a test driver for this interface that performs ..."
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Cited by 823 (41 self)
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that performs random testing to simulate the most general environment the program can operate in; and (3) dynamic analysis of how the program behaves under random testing and automatic generation of new test inputs to direct systematically the execution along alternative program paths. Together, these three
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