OFDM Relay Cognitive Radio Multiple Antennas Resource Allocation Full Duplex Spectrum Sensing Synchronization Spectrum Sharing Interference Cancellation Channel Estimation Feedback Stochastic Geometry Heterogeneous Networks Bi-directional Energy Harvesting relay networks FBMC Equalization interference Duplex CDMA SC-FDMA HetNet interference suppression Ultra Low Power TVWS 5G channel capacity in-band full-duplex system QAM intersymbol interference intercarrier interference quality of service amplify and forward communication Zigbee cellular radio telecommunication traffic 5G mobile communication LTE-TDD distributed mode power uncertainty SCMA frame structure health care antenna arrays body area networks timing misalignment MIMO User association Outdated channel estimation self interference cancellation C-V2V ultra-dense small cell network channel estimation error Full-duplex Timing and frequency offset resource block management UFMC Handoff System level simulation Empty cell Ultra-dense small cell On/off algorithm CoMP Metaheuristics Power control MPA detector End-to-end delay mMTC Short burst transmission Traffic Poisson arrival Capacity Time-division duplex Subband filtering OCBT Waveforms Vehicle-to-vehicle communication Spatial capacity LTE-based V2V Communication range CFO Reliability Uplink SCMA system resource selection maximum likelihood method Vehicular communication V2X P-NOMA partial overlap QR Factorization FS-NOMA Dynamic TDD Number of training blocks cross-link interference user fairness Multi-user Receiver Mode 3 non-orthogonal multiple access
Status : Presented 
Date : 1989-06 
Title : A Hierarchical Neural Networks Involving Nonlinear Spectral Processing 
Authors : Daesik Hong and O. K. Ersoy 
Conference : IEEE International Joint Conference on Neural Networks 
Abstract : Summary form only given, as follows. A new neural network architecture called the hierarchical neural network (HNN) is introduced. The HNN involves a number of stages in which each stage can be a particular neural network (SNN). Between two SNNs there is a nonlinear transformation of those input vectors rejected by the first SNN. The HNN has many desirable properties such as optimized system complexity in the sense of minimized number of stages, high classification accuracy, minimized learning and recall times, and truly parallel architectures in which all SNNs are operating simultaneously without waiting for data from each other. The experiments performed in comparison to multilayered networks with backpropagation training indicated the superiority of the HNN 
URL : http://ieeexplore.ieee.org/xpl/articleDe...ber=118514 

 Ersoy, O.K.; Hong, D.; , "A hierarchical neural network involving nonlinear spectral processing," Neural Networks, 1989. IJCNN., International Joint Conference on , vol., no., pp.624 vol.2, 0-0 1989
doi: 10.1109/IJCNN.1989.118514
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=118514&isnumber=3401

List of Articles
No.
Status Datesort
9 [IEEE IJCNN] Sooyong Choi, KyunByoung Ko and Daesik Hong, "Equalization Techniques Using A Simplified Bilinear Recursive Polynomial Perceptron with Decision Feedback", IJCNN, Jun. 2001 Presented  2001-07 
8 [IEEE IJCNN] Sooyong Choi, KyunByoung Ko and Daesik Hong, "A Multilayer Feedforward Neural Network Having N/4 nodes in Two Hidden Layers", IJCNN, Jun. 2001 file Presented  2001-07 
7 [IEEE IJCNN] KyunByoung Ko, Sooyong Choi, Changeon Kang and Daesik Hong, "A Simplified multiuser Receiver of DS-CDMA System", IJCNN, Jul. 2001 file Presented  2001-07 
6 [IEEE IJCNN] Kyunbyoung Ko, Sooyong Choi and Daesik Hong, "Multi-User Detector with an ability of channel estimation using a RBF network in an MC-CDMA System", IEEE IJCNN, July 2000 Presented  2000-07 
5 [IEEE IJCNN] Sooyong Choi and Daesik Hong, "Equalization Using the Bilinear Recursive Polynomial Perceptron with Decision Feedback", IEEE IJCNN, July 2000 Presented  2000-07 
4 [IEEE IJCNN] Sooyong Choi and Daesik Hong, "A Hybrid Structured Neural Network Receiver in Digital Communication Systems", IEEE IJCNN, July 2000 Presented  2000-07 
3 [IEEE IJCNN] Sooyong Choi and Daesik Hong, "'Performance of RBF equalizer in data storage channels", IEEE IJCNN, Jul. 1999 Presented  1999-07 
2 [IEEE IJCNN] Kyunggoo Lee, Cheolwoo You, Sooyong Choi, Sunghwan Ong and Daesik Hong, "Performance Evaluation of Neural Equalizers for the DVD-ROM System", IEEE IJCNN, May, 1998 Presented  1998-05 
» [IEEE IJCNN] Daesik Hong and O. K. Ersoy, "A Hierarchical Neural Networks Involving Nonlinear Spectral Processing",IEEE IJCNN., June 1989 Presented  1989-06