[PDF] Top 20 A Time-Frequency Feature Fusion Algorithm Based on Neural Network for HRRP
Has 10000 "A Time-Frequency Feature Fusion Algorithm Based on Neural Network for HRRP" found on our website. Below are the top 20 most common "A Time-Frequency Feature Fusion Algorithm Based on Neural Network for HRRP".
A Time-Frequency Feature Fusion Algorithm Based on Neural Network for HRRP
... the fusion method can yield higher performance under high SNR, but under low SNR, the performance drops ...weighted fusion process also enhances the ...the fusion algorithm under 5 dB SNR is ... See full document
9
An Efficient Block based Feature Level Image Fusion Technique using Wavelet Transform and Neural Network
... The fusion process can be performed at different levels of information representation such as pixel level, feature level and symbolic ...image fusion, the simple mathematical operations such as ... See full document
7
Medical image fusion based on pulse coupled neural networks and multi feature fuzzy clustering
... image fusion plays an important role in cli- nical applications such as image-guided surgery, im- age-guided radiotherapy, noninvasive diagnosis, and treatment ...image fusion algorithm based ... See full document
6
MULTI LEVEL GROUP KEY MANAGEMENT TECHNIQUE FOR MULTICAST SECURITY IN MANET
... of time domain and frequency domain to the radar non-contact life- parameter signals and gain its characteristics of extremely low frequency, low SNR, and the easy submerged in strong clutter ...the ... See full document
5
Beat classification of an ecg signal using photoplethysmography and neural network
... same time alike for different types of ...image feature extraction and classification system, the present research work proposes the use of different feature extraction ...image feature ... See full document
6
Multi-task hidden Markov modeling of spectrogram feature from radar high-resolution range profiles
... the frequency domain feature as in [6], this study exploits the spectrogram feature of HRRP data for combining both time domain and frequency domain features, which is a ... See full document
17
Curvelet and Wavelet Image Fusion using Neural Network Algorithm
... is based on a certain anisotropic scaling principle which is quite deferent from the isotropic scaling of ...of time, we feel that the very novel features of the transform - anisotropy, anisotropy scaling - ... See full document
5
A New Retrieval Algorithm Based on Pulse Coupled Neural Network for Biomedical Images
... image feature. Johnson [1] first proposed the time series G(n) = , as image feature where n is the iteration ...the feature vector is based on the total number of the PCNN iterative ... See full document
5
Date Fruits Classification using MLP and RBF Neural Networks
... products, based on video inspection has been stated in ...intelligence neural networks is given in [10]. An algorithm of apples shape setting and identification of their stalk is developed in ... See full document
6
An Image Classification Algorithm Based on Multidomain Convolution Neural Network
... Convolutional Neural Networks (CNNs) have outperformed humans in many computer vision tasks, such as object recognition and image classification, but it is almost impossible to run a large-scale CNN network ... See full document
6
Brain Tumor Segmentation from Multi modality MRI Data Based on Tamura Texture
... is based on the BP neural network algorithm without considering texture information, the kernel function of the algorithm is Gauss kernel ...is based on seeds selection, seeds ... See full document
6
Method of Wireless Sensor Network Data Fusion
... data fusion method based on wireless sensor networks is de- ...signed. Based on the analysis of the structure and learning algorithm of RBF neural networks, a heterogeneous RBF ... See full document
9
Neural Network Based Normalized Fusion Approaches for Optimized Multimodal Biometric Authentication Algorithm
... images. Low resolution images for civil and commercial applications. The preprocessing is used to set up coor- dinate’s alignment and segments the images for feature extraction. Preprocessing of Finger vein takes ... See full document
8
Image Fusion using Lifting Wavelet Transform with Neural Networks for Tumor Detection
... major feature of lifting scheme is that all constructions are represented in spatial the ...efficient algorithm that any wavelet with FIR filters can be factorized into a sequence of lifting steps and ... See full document
6
A Novel Wireless Sensor Node Positioning Algorithm Based on Ant Colony Optimization Algorithm and Neural Network
... of time; the data acquired by neighbouring nodes are similar within a short period of ...data fusion technique should be introduced to the WSN to process and retransmit the original data as ... See full document
13
Freight-Forward Agreement Time series Modelling Based on Artificial Neural Network Models
... applying neural network modelling within the context of crude oil freight rate prediction for the Mediterranean line (Med-Med) using data from 1980 to 1995 and three variables: the actual rate time ... See full document
6
Curvelet Image Fusion using Neural Network and SVM Algorithm
... image fusion process which is suitable for pan-sharpening of multispectral (MS) groups furthermore in view of multi-resolution ...image fusion strategy gives high quality of the spectral content of the ... See full document
5
Study and Evaluation Facial Expressions Recognition Methods
... patterns. Based on time patterns, they presented a plan for representing continuous emotional states by a communication agent on a three-dimensional ... See full document
16
AN EMPIRICAL STUDY ON ARCHITECTURE, CHALLENGES, TAXONOMY FOR ENTERPRISE APPLICATION MODERNIZATION
... a frequency domain signal by using Fast Fourier Transform (FFT) ...extract based on different dimensionality reduction technique such as PCA and ...of feature reduction technique and classifier is ... See full document
9
Complex HRRP Target Recognition Based on Phase and Amplitude Fusion Analysis
... [3], HRRP is a promising signature and more easy to be acquired in actual application, but it is highly sensitive to target-aspect, time-shift and amplitude-scale variations [4–6], so how to extract robust ... See full document
10
Related subjects