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Results for Iterative methods

Publications & Outputs

  1. Energy Efficient Uplink Transmissions in LoRa Networks

    Su, B., Qin, Z. & Ni, Q., 1/08/2020, In : IEEE Transactions on Communications. 68, 8, p. 4960-4972 13 p.

    Research output: Contribution to journalJournal article

  2. Investigation on Estimator of Chirp Rate and Initial Frequency of LFM Signals Based on Modified Discrete Chirp Fourier Transform

    Song, J., Xu, Y., Liu, Y. & Zhang, Y., 1/12/2019, In : Circuits, Systems, and Signal Processing. 38, 12, p. 5861-5882 22 p.

    Research output: Contribution to journalJournal article

  3. Flexible unsupervised feature extraction for image classification

    Liu, Y., Nie, F., Gao, Q., Gao, X., Han, J. & Shao, L., 1/07/2019, In : Neural Networks. 115, p. 65-71 7 p.

    Research output: Contribution to journalJournal article

  4. An iterative coarse-to-fine sub-sampling method for density reduction of terrain point clouds

    Fan, L. & Atkinson, P. M., 19/04/2019, In : Remote Sensing. 11, 8, 11 p., 947.

    Research output: Contribution to journalJournal article

  5. Joint Robust Beamforming and Power-Splitting Ratio Design in SWIPT-Based Cooperative NOMA Systems With CSI Uncertainty

    Yuan, Y., Xu, P., Yang, Z., Ding, Z. & Chen, Q., 1/03/2019, In : IEEE Transactions on Vehicular Technology. 68, 3, p. 2386-2400 15 p.

    Research output: Contribution to journalJournal article

  6. A spectrometer for ultrashort gamma-ray pulses with photon energies greater than 10 MeV

    Behm, K. T., Cole, J. M., Joglekar, A. S., Gerstmayr, E., Wood, J. C., Baird, C. D., Blackburn, T. G., Duff, M., Harvey, C., Ilderton, A., Kuschel, S., Mangles, S. P. D., Marklund, M., McKenna, P., Murphy, C. D., Najmudin, Z., Poder, K., Ridgers, C. P., Sarri, G., Samarin, G. M. & 5 others, Symes, D., Warwick, J., Zepf, M., Krushelnick, K. & Thomas, A. G. R., 11/2018, In : Review of Scientific Instruments. 89, 11, 10 p., 113303.

    Research output: Contribution to journalJournal article

  7. Auto-balanced filter pruning for efficient convolutional neural networks

    Ding, X., Ding, G., Han, J. & Tang, S., 27/04/2018, THE THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE THE THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE THE EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE.. AAAI, p. 6797-6804 8 p. (THE THIRTY-SECOND AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE THE THIRTIETH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE THE EIGHTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE.).

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

  8. Quick verification of concurrent programs by iteratively relaxed scheduling

    Metzler, P., Saissi, H., Bokor, P., Suri, N., T.N., N. (ed.), G., R. (ed.) & M., D. P. (ed.), 30/10/2017, 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE, p. 776-781 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

  9. A non-iterative (trivial) method for posterior inference in stochastic volatility models

    Tsionas, M. G., 1/07/2017, In : Statistics and Probability Letters. 126, p. 83-87 5 p.

    Research output: Contribution to journalJournal article