Showing papers in "Signal Processing in 2017"

TL;DR: An effective and reliable deep learning method known as stacked denoising autoencoder (SDA), which is shown to be suitable for certain health state identifications for signals containing ambient noise and working condition fluctuations, is investigated.

TL;DR: Simulations and performance evaluations show that the proposed system is able to produce a one-dimension (1D) chaotic system with better chaotic performances and larger chaotic ranges compared with the previous chaotic maps.

TL;DR: The work provides some bases for further optimizing attack on the Fridrich's chaotic image encryption scheme and its variants and extension of the attack idea to Chen's scheme andIts variants is briefly evaluated.

TL;DR: Simulation results and performance analyses verify the effectiveness of the proposed encryption algorithm, which can achieve the image data security and image appearance security simultaneously, and the size of the cipher image and original image is equal, it does not require additional transmission bandwidth and storage space.

TL;DR: This work provides an overview on the main signal processing techniques employed in road engineering, and theoretical insights and instructions on the proper use of the processing in relation to the quality of the data acquired and the purposes of the surveys.

TL;DR: The local cut-off frequency is adaptively designed by fully facilitating the instantaneous amplitude and frequency information and is able to improve the frequency separation performance, as well as the stability under low sampling rates.

TL;DR: This work reviews the various methods to create a radiomap and examines the various aspects such as the density of access points (APs) and impact of an outdated signature map which affect the performance of fingerprinting localization.

TL;DR: A new fragile watermarking scheme with high-quality recovery capability based on overlapping embedding strategy that can achieve better quality of recovered image compared with some of state-of-the-art schemes.

TL;DR: This paper proposes an asymmetric image encryption algorithm for the advantages that the key groups and the number of keys in secret information transmission among multiple people are very small, and key transmission mode is relatively simple and secure.

TL;DR: This paper presents a tutorial on the main Gaussian filters that are used for state estimation of stochastic dynamic systems and describes the main concept of state estimation based on the Bayesian paradigm and Gaussian assumption of the noise.

TL;DR: Simulations and analysis results show that cooperation of AES and EC random numbers makes great results in randomness and image encryption field, and the results of the evaluation prove the effectiveness and security of the proposed method.

TL;DR: A lossless edge maps based image cryptosystem for medical image that has a strong resistance against various security attacks and outperforms other state-of-the-art methods.

TL;DR: An active contour model which combines region-scalable fitting energy and optimized Laplacian of Gaussian (LoG) energy is proposed for image segmentation and has a higher segmentation accuracy and efficiency than other major region-based models.

TL;DR: The proposed adaptive parameterless EWT (APEWT) method could effectively fulfill the fault diagnosis of rotor rubbing and show a better effect than EMD and EEMD methods, according to analysis of experiment data.

TL;DR: Five theoretical requirements which a generic ESS function should satisfy are listed, allowing us to classify different ESS measures, and several examples are provided involving, for instance, the geometric mean of the weights, the discrete entropy and the Gini coefficient.

TL;DR: This work extends the scalar innovation into an innovation vector and presents a multi-innovation gradient parameter estimation algorithm for a state-space system with d-step state-delay by means of the multi-invention identification theory.

TL;DR: A parts-based 2D DDL scheme is introduced and evaluated for simultaneous denoising and interpolation of seismic data and a special case of versatile non-negative matrix factorization (VNMF) is used to learn a dictionary.

TL;DR: Experiments and comparisons show that BBE-RDHEI has an embedding rate nearly twice larger than the state-of-the-art algorithms, generates the marked decrypted images with high quality, and is able to withstand the brute-force, differential, noise and data loss attacks.

TL;DR: Experimental results and performance analysis demonstrate that the proposed image cryptosystem has acceptable speed, good robustness and outperforms some existing image encryption schemes to counteract the recognized attacks.

TL;DR: This paper proposes an improved edge-based level set method combining local regional fitting information by applying the proposed variable regional coefficient and the improved ESF to the energy function of level set function and shows that the method is efficient and robust.

TL;DR: The numerical experiments show that the instantaneous frequency-embedded synchrosqueezing wavelet transform (IFE-SST) outperforms the CWT-based SST in IF estimation and separation of multicomponent signals.

TL;DR: The performance of the proposed RDH approach is largely improved in encrypted images, which shows the effectiveness of the suggested method.

TL;DR: A general model to characterize MCCSs, where instantaneous frequencies (IFs) and instantaneous amplitudes (IAs) of the intrinsic chirp components (ICCs) are modeled as Fourier series are developed and the decomposition problem boils down to identifying the developed model.

TL;DR: The direction of arrival (DOA) estimation for noncircular sources in multiple-input multiple-output (MIMO) radar is dealt with by a novel nuclear norm minimization (NNM) framework that provides superior DOA estimation performance and higher angular resolution due to exploiting the extended array aperture and block-sparse information.

TL;DR: By employing the Wirtinger inequality and extended Jensen inequality, some sufficient conditions of the sampled-data control for T-S fuzzy systems are established, which are efficiently solved by using standard available numerical packages.

TL;DR: A novel subspace method is proposed to reconstruct the interference-plus-noise covariance matrix (IPNCM) according to its definition and estimate the corresponding parameters, namely the SVs and powers of all interferences.

TL;DR: Both simulated and real data experiments illustrate the higher performance of the proposed STWNNM for HSI mixed denoising, by comparing with other state-of-the-art TV-regularized low rank based methods.

TL;DR: A variable initial value scheme is proposed to attenuate the non-locality of fractional order calculus and to ensure the convergence of the proposed FOLMS algorithm to remove the contradiction between rapidity and accuracy.

TL;DR: The resulting accurate continuous–discrete unscented Kalman filter is based on adaptive solvers with automatic global error control for treating numerically the moment differential equations arising in the mean and covariance calculation of propagated Gaussian density.

TL;DR: This paper is concerned with the distributed fusion filtering problem for networked stochastic uncertain systems with white multiplicative noises and develops a new augmented model with a lower-dimension state vector based on the well-known fusion algorithm weighted by matrices in the linear minimum variance sense.