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Training with Noise is Equivalent to Tikhonov Regularization
 Neural Computation
, 1994
"... It is well known that the addition of noise to the input data of a neural network during training can, in some circumstances, lead to significant improvements in generalization performance. Previous work has shown that such training with noise is equivalent to a form of regularization in which an ex ..."
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Cited by 158 (0 self)
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It is well known that the addition of noise to the input data of a neural network during training can, in some circumstances, lead to significant improvements in generalization performance. Previous work has shown that such training with noise is equivalent to a form of regularization in which
Wireless Network Information Flow: A Deterministic Approach
, 2009
"... In contrast to wireline networks, not much is known about the flow of information over wireless networks. The main barrier is the complexity of the signal interaction in wireless channels in addition to the noise in the channel. A widely accepted model is the the additive Gaussian channel model, and ..."
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Cited by 296 (42 self)
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In contrast to wireline networks, not much is known about the flow of information over wireless networks. The main barrier is the complexity of the signal interaction in wireless channels in addition to the noise in the channel. A widely accepted model is the the additive Gaussian channel model
Secure Transmission with Multiple Antennas: The MISOME Wiretap Channel
, 2007
"... The role of multiple antennas for secure communication is investigated within the framework of Wyner’s wiretap channel. We characterize the secrecy capacity in terms of generalized eigenvalues when the sender and eavesdropper have multiple antennas, the intended receiver has a single antenna, and t ..."
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Cited by 240 (19 self)
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, and the channel matrices are fixed and known to all the terminals, and show that a beamforming strategy is capacityachieving. In addition, we show that in the high signaltonoise (SNR) ratio regime the penalty for not knowing eavesdropper’s channel is small—a simple “secure spacetime code ” that can be thought
Blind Source Separation by Sparse Decomposition in a Signal Dictionary
, 2000
"... Introduction In blind source separation an Nchannel sensor signal x(t) arises from M unknown scalar source signals s i (t), linearly mixed together by an unknown N M matrix A, and possibly corrupted by additive noise (t) x(t) = As(t) + (t) (1.1) We wish to estimate the mixing matrix A and the M ..."
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Cited by 274 (34 self)
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Introduction In blind source separation an Nchannel sensor signal x(t) arises from M unknown scalar source signals s i (t), linearly mixed together by an unknown N M matrix A, and possibly corrupted by additive noise (t) x(t) = As(t) + (t) (1.1) We wish to estimate the mixing matrix A and the M
On Beamforming with Finite Rate Feedback in Multiple Antenna Systems
, 2003
"... In this paper, we study a multiple antenna system where the transmitter is equipped with quantized information about instantaneous channel realizations. Assuming that the transmitter uses the quantized information for beamforming, we derive a universal lower bound on the outage probability for any f ..."
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Cited by 272 (14 self)
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finite set of beamformers. The universal lower bound provides a concise characterization of the gain with each additional bit of feedback information regarding the channel. Using the bound, it is shown that finite information systems approach the perfect information case as (t 1)2 , where B
Adaptive Coded Modulation for Fading Channels
 IEEE TRANS. COMMUN
, 1998
"... We apply coset codes to adaptive modulation in fading channels. Adaptive modulation is a powerful technique to improve the energy efficiency and increase the data rate over a fading channel. Coset codes are a natural choice to use with adaptive modulation since the channel coding and modulation desi ..."
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Cited by 204 (11 self)
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designs are separable. Therefore, trellis and lattice codes designed for additive white Gaussian noise (AWGN) channels can be superimposed on adaptive modulation for fading channels, with the same approximate coding gains. We first describe the methodology for combining coset codes with a general class
Analysis of sumproduct decoding of lowdensity paritycheck codes using a Gaussian approximation
 IEEE TRANS. INFORM. THEORY
, 2001
"... Density evolution is an algorithm for computing the capacity of lowdensity paritycheck (LDPC) codes under messagepassing decoding. For memoryless binaryinput continuousoutput additive white Gaussian noise (AWGN) channels and sumproduct decoders, we use a Gaussian approximation for message densi ..."
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Cited by 244 (2 self)
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Density evolution is an algorithm for computing the capacity of lowdensity paritycheck (LDPC) codes under messagepassing decoding. For memoryless binaryinput continuousoutput additive white Gaussian noise (AWGN) channels and sumproduct decoders, we use a Gaussian approximation for message
Secure communication over fading channels
, 2007
"... The fading broadcast channel with confidential messages (BCC) is investigated, where a source node has common information for two receivers (receivers 1 and 2), and has confidential information intended only for receiver 1. The confidential information needs to be kept as secret as possible from rec ..."
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Cited by 186 (21 self)
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receiver 2. The broadcast channel from the source node to receivers 1 and 2 is corrupted by multiplicative fading gain coefficients in addition to additive Gaussian noise terms. The channel state information (CSI) is assumed to be known at both the transmitter and the receivers. The parallel BCC
Communication by energy modulation: The additive exponential noise channel
 IEEE Trans. Inform. Theory
, 2011
"... Abstract—Communication across an additive exponential noise (AEN) channel is studied. The AEN channel is derived from a continuoustime Gaussian channel by assuming decoherence between the signal and noise components. Decoherence renders impossible the use of the complex amplitude and information is ..."
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Cited by 3 (0 self)
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Abstract—Communication across an additive exponential noise (AEN) channel is studied. The AEN channel is derived from a continuoustime Gaussian channel by assuming decoherence between the signal and noise components. Decoherence renders impossible the use of the complex amplitude and information
Coding and Modulation for the Additive Exponential Noise Channel
"... Abstract—Communication across an additive exponential noise (AEN) channel is studied. Constellations are designed for low signaltonoise ratio, where the minimum energy per bit is not universally attained by all modulations, and for high signaltonoise ratio, where an equiprobable nonuniform const ..."
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Abstract—Communication across an additive exponential noise (AEN) channel is studied. Constellations are designed for low signaltonoise ratio, where the minimum energy per bit is not universally attained by all modulations, and for high signaltonoise ratio, where an equiprobable non
Results 11  20
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3,925