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This paper introduces the SHRC-Ginkgo speech synthesis system for Blizzard Challenge 2013. A unit selection based approach is adopted to develop our speech synthesis system using audiobook speech corpus. Aiming at roughly labeled corpora with several hundred hours of speech, our system adopts lightly-supervised acoustic model training of speech recognition(More)
Spike detection from high data rate neural recordings is desired to ease the bandwidth bottleneck of bio-telemetry. An appropriate spike detection method should be able to detect spikes under low signal-to-noise ratio (SNR) while meeting the power and area constraints of implantation. This paper introduces a spike detection system utilizing lifting-based(More)
—Spike detection is an essential first step in the analysis of neural recording signals. A new spike detection hardware architecture combining absolute threshold method and stationary wavelet transform (SWT) is described. The method enables spike detection with 90% accuracy even when the signal-to-noise is-1dB. A noise monitoring block was implemented to(More)
— Multi-channel neural signal recordings need high data compression and efficient data transmission. Our previous work has shown a practical data compression solution based on discrete wavelet transform, multi-level thresholding and run length encoding. This paper presents a custom designed communication protocol for bidirectional data telemetry to and from(More)
Within the statistical learning framework, this paper studies the regression model associated with the correntropy induced losses. The correntropy, as a similarity measure, has been frequently employed in signal processing and pattern recognition. Motivated by its empirical successes, this paper aims at presenting some theoretical understanding towards the(More)
In this letter, we propose a rank-one tensor updating algorithm for solving tensor completion problems. Unlike the existing methods which penalize the tensor by using the sum of nuclear norms of unfolding matrices, our optimization model directly employs the tensor nuclear norm which is studied recently. Under the framework of the conditional gradient(More)
In this paper, we study a class of biquadratic optimization problems. We first relax the original problem to its semidefinite programming (SDP) problem and discuss the approximation ratio between them. Under some conditions, we show that the relaxed problem is tight. Then we consider how to approximately solve the problems in polynomial time. Under several(More)