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recognition of colors in eeg

Аналоги для Recognition of Colors in EEG
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Recognition of Colors in EEG

7790 рублей

Аналоги для A Survey of EEG Signal Processing Techniques
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A Survey of EEG Signal Processing Techniques

4839 рублей

Аналоги для Mean Threshold and ARNN Algorithms for Classification of EEG Commands
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Mean Threshold and ARNN Algorithms for Classification of EEG Commands

3549 рублей

Аналоги для Sleep Stages Classification Using WT And ANN
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Sleep Stages Classification Using WT And ANN

4839 рублей

Аналоги для EMD-Chaos based analysis of EEG signals for early seizure detection
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EMD-Chaos based analysis of EEG signals for early seizure detection

5790 рублей

Аналоги для Evolving Probabilistic Spiking Neural Networks
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Evolving Probabilistic Spiking Neural Networks

7390 рублей

Аналоги для Advanced Visualization of EEG Data
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Advanced Visualization of EEG Data

4929 рублей

Аналоги для Feature extraction and classification technique for chronic alcoholism
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Feature extraction and classification technique for chronic alcoholism

4929 рублей

Аналоги для Translation Of Human Thoughts Into Machine Motion
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Translation Of Human Thoughts Into Machine Motion

5790 рублей

Аналоги для An EEG-based Model of Daytime Vigilance Trends
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An EEG-based Model of Daytime Vigilance Trends

8890 рублей

Аналоги для Handwritten Marathi Numeral Recognition
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Handwritten Marathi Numeral Recognition

4839 рублей

Аналоги для fMRI Artifact Correction in EEG and EMG Data
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fMRI Artifact Correction in EEG and EMG Data

6390 рублей

Купить Recognition of Colors in EEG в Москве и СПБ с доставкой недорого

recognition of colors in eeg характеристики

EEG signal processing is one of the hottest areas of research in digital signal processing applications and biomedical research. Analysis of EEG signals provides a crucial tool for diagnosis of neurobiological diseases. The problem of EEG signal classification into different sleep stages is primarily a pattern recognition problem using extracted features. Many methods of feature extraction have been applied to extract the relevant characteristics from a given EEG data. The EEG data was collected from publicly available source. The data consists of different age male & female recordings for a whole night of 8 hrs. The feature extraction was done by computing the Discrete Wavelet Transform and ANN using BP algorithm.The wavelet transform coefficients compress the number of data points into few features. The Approximation & Detailed coefficients obtained from Sub-band coding method provide important features of the EEG signals. In this project we have applied optimization techniques to reduce the computation complexity of the network without affecting the accuracy of the classification. Classification of the EEG data using neural network provides robust and improved Performance

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7790 рублей