Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
Volume 7 , Issue 3
Showing 1-11 articles out of 11 articles from the selected issue
Special Section on Rigorous Nonlinear Analysis
Regular Section
  • Kodai Ueyoshi, Takao Marukame, Tetsuya Asai, Masato Motomura, Alexandr ...
    Type: Paper
    2016 Volume 7 Issue 3 Pages 395-406
    Published: 2016
    Released: July 01, 2016
    JOURNALS FREE ACCESS
    Remarkable hardware robustness of deep learning is revealed from an error-injection analysis performed using a custom hardware model implementing parallelized restricted Boltzmann machines (RBMs). RBMs used in deep belief networks (DBNs) demonstrate robustness against memory errors during and after learning. Fine-tuning has a significant impact on the recovery of accuracy under the presence of static errors that may modify structural data of RBMs. The proposed hardware networks with fine-graded memory distribution are observed to tolerate memory errors, thereby resulting in a reliable deep learning hardware platform, potentially suitable to safety-critical embedded applications.
    Download PDF (680K)
  • Hiroya Tanaka, Takaya Yamazato, Yukihiro Tadokoro, Shintaro Arai
    Type: Paper
    2016 Volume 7 Issue 3 Pages 407-418
    Published: 2016
    Released: July 01, 2016
    JOURNALS FREE ACCESS
    This paper discusses the stochastic resonance (SR) effect in a binary communication system for subthreshold signal reception. We focus on the problem of no communication when received signal strength is below receiver sensitivity. Subthreshold signal reception requires a device that exhibits SR, such as a Schmitt trigger or a comparator. Previously, we proposed an alternative three-level device and demonstrated its high performance for subthreshold signal reception in an SR receiver. In the present study, we show that our proposed three-level device outperforms the three devices and discuss reasons for this superior performance. Contributions of our present paper are twofold: first, we analytically derive bit error rate (BER) performances of SR receivers installed with a Schmitt trigger and a comparator;second, we compare performances of the Schmitt trigger, comparator, and three-level device.
    Download PDF (603K)
  • Vikas Paduvalli, Robert Taylor, Louis Hunt, Poras T Balsara
    Type: Paper
    2016 Volume 7 Issue 3 Pages 419-429
    Published: 2016
    Released: July 01, 2016
    JOURNALS FREE ACCESS
    This paper presents the theory and implementation of the non-linear control method of Input to Output Linearization (IOL) for boost DC-DC switching power converters operating in continuous inductor current mode. The paper examines the non-linear and non-minimum phase nature of boost converters. The limitations of IOL control on boost converters have been outlined. It has been shown that these limitations are overcome by addressing the non-minimum phase nature in boost converters. Using analytical and experimental methods, it is demonstrated that IOL control scheme compensates the non-linear boost converter to achieve wide range of output voltages with excellent response to load and duty cycle variations.
    Download PDF (5765K)
feedback
Top