OFDM
Relay
Cognitive Radio
Multiple Antennas
Resource Allocation
Full Duplex
Spectrum Sensing
Synchronization
Spectrum Sharing
Interference Cancellation
Channel Estimation
Feedback
Stochastic Geometry
Bi-directional
Energy Harvesting
Heterogeneous Networks
FBMC
HetNet
Equalization
relay networks
Ultra Low Power
TVWS
MIMO
interference
SC-FDMA
CDMA
Duplex
channel capacity
interference suppression
5G
Reliability
C-V2V
in-band full-duplex system
OCBT
CLI
body area networks
5G mobile communication
antenna arrays
NR positioning
health care
Resource sharing
Location-based
LTE-TDD
FS-NOMA
Power allocation
OTDOA
hybrid
control overhead
estimated position overlapping
resource block management
amplify and forward communication
power uncertainty
CoMP
quality of service
cellular radio
Rat-dependent positioning
telecommunication traffic
Handoff
Femtocell
inter user interference
UFMC
mode selection
GFDM
QAM
Zigbee
frame structure
Vehicular communication
Vehicle-to-vehicle communication
non-orthogonal multiple access
QR Factorization
Spatial capacity
LTE-based V2V
Number of training blocks
Communication range
user fairness
Mode 3
resource selection
distributed mode
maximum likelihood method
Metaheuristics
cross-link interference
Dynamic TDD
Uplink SCMA system
V2X
DQN
estimated position updating
—Device-to-device (D2D)
D-TDD
dynamic HetNet
indoor positioning
spectrum partitioning
- Computation offloading
multi-access edge computing
P-NOMA
partial overlap
Subband filtering
Multi-user Receiver
reinforcement learning
RSRP weighting
smart factory
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Daesik Hong and O. K. Ersoy, "Neural Networks Learning Paradigms Involving Nonlinear Spectral Processing", IEEE ICASSP, May 1989
[IEEE ICASSP]
조회 56693
Status : | Presented |
---|---|
Date : | 1989-05 |
Title : | Neural Networks Learning Paradigms Involving Nonlinear Spectral Processing |
Authors : | Daesik Hong and O. K. Ersoy |
Conference : | IEEE International Conference on Acoustics, Speech, and Signal Processing |
Abstract : | Two neural network architectures involving nonlinear spectral transformations are described. The first architecture involves generalization of nonlinear matched-filtering techniques, yielding a network that is very fast in learning and recall as well as highly accurate in classification. The second architecture is hierarchical with a number of stages; after each stage, error detection is carried out, followed by nonlinear spectral transformations when the error measure is above threshold |
URL : | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=266794 |
Ersoy, O.K.; Hong, D.; , "Neural network learning paradigms involving nonlinear spectral processing,"Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on , vol., no., pp.1775-1778 vol.3, 23-26 May 1989
doi: 10.1109/ICASSP.1989.266794
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=266794&isnumber=6677
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