Results 111 to 120 of about 26,804 (294)
Forward Stepwise Deep Autoencoder-based Monotone Nonlinear Dimensionality Reduction Methods. [PDF]
Fong Y, Xu J.
europepmc +1 more source
Wafer‐scale two‐dimensioanl In2Se3 oxidized into InOx on sodium‐embedded beta‐alumina enables multifunctional reconfigurable electronics. Sodium ions accumulate within distinct spatial distribution under drain‐controlle and gate‐controlled operation. Drain‐control operation gives controllability of ultraviolet‐driven optoelectronic synaptic conductance
Jinhong Min +13 more
wiley +1 more source
Efficient Parallel Algorithm for Nonlinear Dimensionality Reduction on GPU [PDF]
[[abstract]]Advances in nonlinear dimensionality reduction provide a way to understand and visualize the underlying structure of complex data sets. The performance of large-scale nonlinear dimensionality reduction is of key importance in data mining ...
Tsung Tai Yeh;Tseng-Yi Chen;Wei-Kuan Shih;Yeh-Chiu Chen
core
Riemannian manifold learning for nonlinear dimensionality reduction [PDF]
In recent years, nonlinear dimensionality reduction (NLDR) techniques have attracted much attention in visual perception and many other areas of science. We propose an efficient algorithm called Riemannian manifold learning (RML).
Hongbin Zha +8 more
core +1 more source
Historical Foundation and Practical Guideline for Ferroelectric Switching Kinetic Studies
The P and U pulses in the conventional PUND measurements are not identical because of the interplay between switching current and the measurement circuit components. This circuit effect can lead to a shift in polarization transients and misinterpreted physics in the switching kinetics.
Yi Liang, Pat Kezer, John T. Heron
wiley +1 more source
Advances in Sustainable and Wearable Textile Based Soft Robotics
This Review examines advances in wearable textile‐based soft robotics, focusing on sustainable materials, integrated sensing, and scalable actuation. It discusses manufacturing and system integration across healthcare, assistive robotics, prosthetics, and human–machine interfaces, and highlights key challenges in circular design, including life‐cycle ...
Zahir Abbas +6 more
wiley +1 more source
Nonlinear dimensionality reduction methods in climate data analysis [PDF]
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality.
Ross, Ian
core
Gaussian processes autoencoder for dimensionality reduction [PDF]
Learning low dimensional manifold from highly nonlinear data of high dimensionality has become increasingly important for discovering intrinsic representation that can be utilized for data visualization and preprocessing.
Cai, Z. +7 more
core +1 more source
Velocity‐Tunable Exciton‐Photon Hybridization in Cathodoluminescence
Transition‐radiation resonances in suspended thin crystals hybridise with excitonic transitions under free‐electron excitation. By tuning the electron energy, the photonic resonances are continuously detuned across the exciton states, enabling controllable exciton–photon hybridisation below the diffraction limit without altering the system geometry ...
Sven Ebel +4 more
wiley +1 more source
Nonlinear Dimensionality Reduction by Manifold Unfolding [PDF]
Every second, an enormous volume of data is being gathered from various sources and stored in huge data banks. Most of the time, monitoring a data source requires several parallel measurements, which form a high-dimensional sample vector.
Khajehpour Tadavani, Pooyan
core

