232 research outputs found
Observer and Command-Filter-Based Adaptive Fuzzy Output Feedback Control of Uncertain Nonlinear Systems
Command Filter-Based Adaptive Optimal Control of Uncertain Nonlinear Systems with Quantized Input
Event-Triggered Distributed Fixed-Time Adaptive Attitude Control With Prescribed Performance for Multiple QUAVs
Cross-lingual Alzheimer's Disease detection based on paralinguistic and pre-trained features
We present our submission to the ICASSP-SPGC-2023 ADReSS-M Challenge Task,
which aims to investigate which acoustic features can be generalized and
transferred across languages for Alzheimer's Disease (AD) prediction. The
challenge consists of two tasks: one is to classify the speech of AD patients
and healthy individuals, and the other is to infer Mini Mental State
Examination (MMSE) score based on speech only. The difficulty is mainly
embodied in the mismatch of the dataset, in which the training set is in
English while the test set is in Greek. We extract paralinguistic features
using openSmile toolkit and acoustic features using XLSR-53. In addition, we
extract linguistic features after transcribing the speech into text. These
features are used as indicators for AD detection in our method. Our method
achieves an accuracy of 69.6% on the classification task and a root mean
squared error (RMSE) of 4.788 on the regression task. The results show that our
proposed method is expected to achieve automatic multilingual Alzheimer's
Disease detection through spontaneous speech.Comment: accepted by ICASSP 202
Event-Triggered Adaptive Fuzzy Finite-Time Output Feedback Control for Stochastic Nonlinear Systems With Input and Output Constraints
A new result on observer-based sliding mode control design for a class of uncertain Ito^ stochastic delay systems
© 2017 The Franklin Institute This paper develops a new observer-based sliding mode control (SMC) scheme for a general class of Ito^ stochastic delay systems (SDS). The key merit of the presented scheme lies in its simplicity and integrity in design process of the traditional sliding mode observer (SMO) strategy, i.e., the state observer and sliding surface design as well as the associated sliding mode controller synthesis. For guaranteeing to use the scheme, a new LMIs-based criterion is established to ensure the exponential stability of the underlying sliding mode dynamics (SMDs) in mean-square sense with H∞ performance. A bench test example is provided to numerically demonstrate the efficacy of the scheme and illustrate the application procedure for potential readers/users with interest in their ad hoc applications and methodology expansion
Unified Joint Matrix-Monotonic Optimization of MIMO Training Sequences and Transceivers
Channel estimation and transmission constitute the most fundamental
functional modules of multiple-input multiple-output (MIMO) communication
systems. The underlying key tasks corresponding to these modules are training
sequence optimization and transceiver optimization. Hence, we jointly optimize
the linear transmit precoder and the training sequence of MIMO systems using
the metrics of their effective mutual information (MI), effective mean squared
error (MSE), effective weighted MI, effective weighted MSE, as well as their
effective generic Schur-convex and Schur-concave functions. Both statistical
channel state information (CSI) and estimated CSI are considered at the
transmitter in the joint optimization. A unified framework termed as joint
matrix-monotonic optimization is proposed. Based on this, the optimal precoder
matrix and training matrix structures can be derived for both CSI scenarios.
Then, based on the optimal matrix structures, our linear transceivers and their
training sequences can be jointly optimized. Compared to state-of-the-art
benchmark algorithms, the proposed algorithms visualize the bold explicit
relationships between the attainable system performance of our linear
transceivers conceived and their training sequences, leading to implementation
ready recipes. Finally, several numerical results are provided, which
corroborate our theoretical results and demonstrate the compelling benefits of
our proposed pilot-aided MIMO solutions.Comment: 29 pages, 7 figure
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