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You searched for subject:(Artificial nervous system). Showing records 1 – 3 of 3 total matches.

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Reykjavík University

1. Vilhjálmur Rúnar Vilhjálmsson 1987-. Wisebeat : artificial sound sampling with deep convolutional generative adversarial networks .

Degree: 2020, Reykjavík University

Hljómgervill á í veflausnarformi, markmið afurðar er að skoða aðkomu andstæðu tauganeta hvort hægt sé að framkalla ný hljóð fyrir tónlistarmenn með hjálp gervigreindar.

Subjects/Keywords: Tölvunarfræði; Hljóðgervill; Gervigreind; Taugakerfi; Computer science; Synthesizer; Artificial intelligence; Nervous system

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

1987-, V. R. V. (2020). Wisebeat : artificial sound sampling with deep convolutional generative adversarial networks . (Thesis). Reykjavík University. Retrieved from http://hdl.handle.net/1946/34914

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

1987-, Vilhjálmur Rúnar Vilhjálmsson. “Wisebeat : artificial sound sampling with deep convolutional generative adversarial networks .” 2020. Thesis, Reykjavík University. Accessed September 18, 2020. http://hdl.handle.net/1946/34914.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

1987-, Vilhjálmur Rúnar Vilhjálmsson. “Wisebeat : artificial sound sampling with deep convolutional generative adversarial networks .” 2020. Web. 18 Sep 2020.

Vancouver:

1987- VRV. Wisebeat : artificial sound sampling with deep convolutional generative adversarial networks . [Internet] [Thesis]. Reykjavík University; 2020. [cited 2020 Sep 18]. Available from: http://hdl.handle.net/1946/34914.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

1987- VRV. Wisebeat : artificial sound sampling with deep convolutional generative adversarial networks . [Thesis]. Reykjavík University; 2020. Available from: http://hdl.handle.net/1946/34914

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

2. Nirmala Devi, M. VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -.

Degree: Information and Communication Engineering, 2014, Anna University

A Biological Neural Network BNN forms the Central Nervous newlineSystem which has highly interconnected neurons to co ordinate all the newlinefunctions like reading and thinking Artificial Neurons are simple newlineabstractions of biological neurons programmed in software or modeled in newlinehardware Networks of artificial neurons known as Artificial Neural Networks newline ANN have a fraction of power of biological neural structures and they can newlinebe trained to solve many complex problems An ANN has the ability to learn newlineand it had been realized in software But learning is a recursive process newlineinvolving multiple iterations which takes a long time when implemented in newlinesoftware However availability of powerful resources at affordable cost has newlineopened up the interesting possibility of realizing ANN in hardware The focus newlineof the present work is on Very Large Scale Integration VLSI hardware newlinerealization of ANN so as to achieve flexibility portability and adaptability newline newline

reference p.169-183

Advisors/Committee Members: Arumugam, S.

Subjects/Keywords: Artificial Neural Networks; Biological Neural Network; Central Nervous System; Very Large Scale Integration

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Nirmala Devi, M. (2014). VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/26986

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Nirmala Devi, M. “VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -.” 2014. Thesis, Anna University. Accessed September 18, 2020. http://shodhganga.inflibnet.ac.in/handle/10603/26986.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Nirmala Devi, M. “VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -.” 2014. Web. 18 Sep 2020.

Vancouver:

Nirmala Devi M. VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -. [Internet] [Thesis]. Anna University; 2014. [cited 2020 Sep 18]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26986.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Nirmala Devi M. VLSI realization of artificial neural Networks using digital and mixed Signal hardware; -. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/26986

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Northeastern University

3. Westphal, Anthony. Controlling a lamprey-based robot with an electronic nervous system.

Degree: PhD, Department of Biology, 2012, Northeastern University

We have developed a biomimetic underwater robot based on the biomechanics and neural control systems of the sea lamprey, to better understand how sensory systems modulate behavior and demonstrate the advantages of neuronal circuits over algorithmic control. The robot has an electronic nervous system (ENS) consisting of discrete-time map-based neurons and synapses. The neurons and synapses are connected to form networks. These networks consist of sets of segmental central pattern generator (CPG) that produce locomotor control signals. To allow the robot to reactively navigate through its environment, we developed an exteroceptive sensory suite consisting of an accelerometer, tilt sensor, compass and sonar short baseline array (SBA). Given a goal such as a destination the robot makes decisions reactively, based on its sensory inputs, rather than a pre-determined algorithm. Compensation for impediments by nested exteroceptive reflexes allows the robot to navigate reactively in an unpredictable environment.

Subjects/Keywords: biomimetic robot; electronic nervous system; sea lamprey; Artificial Intelligence and Robotics; Biology; Neuroscience and Neurobiology

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Westphal, A. (2012). Controlling a lamprey-based robot with an electronic nervous system. (Doctoral Dissertation). Northeastern University. Retrieved from http://hdl.handle.net/2047/d20004876

Chicago Manual of Style (16th Edition):

Westphal, Anthony. “Controlling a lamprey-based robot with an electronic nervous system.” 2012. Doctoral Dissertation, Northeastern University. Accessed September 18, 2020. http://hdl.handle.net/2047/d20004876.

MLA Handbook (7th Edition):

Westphal, Anthony. “Controlling a lamprey-based robot with an electronic nervous system.” 2012. Web. 18 Sep 2020.

Vancouver:

Westphal A. Controlling a lamprey-based robot with an electronic nervous system. [Internet] [Doctoral dissertation]. Northeastern University; 2012. [cited 2020 Sep 18]. Available from: http://hdl.handle.net/2047/d20004876.

Council of Science Editors:

Westphal A. Controlling a lamprey-based robot with an electronic nervous system. [Doctoral Dissertation]. Northeastern University; 2012. Available from: http://hdl.handle.net/2047/d20004876

.