In this paper,we addressed a new method to estimate the depth of anesthesia based on Hilbert-Huang transforms.

We introduce some speech enhancement algorithms and Hilbert-Huang transforms theory (HHT).

As a new time-frequency method,Hilbert-Huang transform was used to process these signals and the eigenvalue frequencies,the amplitudes and the different appearance times were obtained.

The proposed HVD method was based on the Hilbert transform(HT),just as Hilbert-Huang transform(HHT),but did not involve complicated empirical mode decomposition(EMD).

The Hilbert-Huang transform(HHT) is a new method of time-frequency spectrum treatment that calls for the decomposition of time sequenced data by empirical modes(EMD) which is followed by a Hilbert transform (HT).

The Hilbert-Huang Transformation (HHT) consists of the following steps: First, decomposition of time sequenced data by empirical modes (EMD) followed by a Hilbert transformation to obtain a new method of spectrum treatment.

To deal with the problem of ineffective extraction in underwater target feature extraction methods based on traditional time-frequency analysis,a new time-frequency analysis method,the Hilbert-Huang Transform(HHT) was applied.

Medical Image Retrieval Based on Hilbert-Huang Transform;

Hilbert-Huang transform spectrum and its application in seismic signal analysis;

Time-frequency spectral analysis of seismic data based on Hilbert-Huang transform

RESEARCH ON THE UNIFORM THEORETICAL BASIS FOR HILBERT-HUANG TRANSFORM(HHT);

The unorderly noise signal of the ultrasonic motor is decomposed into Hilbert spectrum with two main frequency bands by HHT.

The Hilbert-huang transform(HHT) is used to analyze the signal of vehicle weigh-in-motion.

This paper uses the Empirical Mode Decomposition (EMD) of Hilbert-Huang Transform (HHT) to solve the problem, and firstly proposes a novel algorithm of endpoint detection of.