Computer Logical Design Laboratory

Tsuneo Tsukahara Professor	Robert H. Fujii Associate Professor

The following researches are progressing in Computer Logical Design Laboratory: Tsuneo Tsukahara: Software-Defined Radio Receivers Related to this topic, the following work was done in 2007. A Spectrum-Analyzing Method for Multi-band Wireless Receivers: Recently the demand for wireless systems such as sensor networks has been rapidly growing. However, radio-wave resources are limited and invaluable especially in these days. Therefore, software-defied radios (SDRs) and cognitive radios, which is a principal application of SDR, can be the key to greatly improving frequency-spectrum efficiency. SDRs demand flexibility and reconfigurability in RF (Radio Frequency) circuits. Therefore, a frequency-efficient wireless transceiver architecture is indispensable. In 2006, we proposed a multi-band wireless receiver using a spectrum-analyzing method. In a receive mode, radio frequency (RF) signals are first amplified and converted to intermediate frequency (IF) signals less than about 10 MHz using mixers or frequency converters. In a spectrum-analyzing method, we use Fourier-series expansion of IF signals in the analog-signal domain because undesired strong signals should be attenuated before analog to digital (A/D) converters to save the number of resolution bits of A/D converters. Coefficients of the Fourier series are calculated using an analog multiplier and an integrator. Because IF frequencies of undesired strong signals are known, their coefficients are forced to zero, thereby being attenuated. Because Fourier-series coefficients of desired signals coming from different radio bands are simultaneously obtained, we can select suitable radio bands for stable communication. Robert Fujii: Neural Networks Due to the amazingly complex and numerous neural connections and the huge number of neurons present in the brain, only phenomenological system level notions about the workings of an entire mammalian brain are currently known. At the brain sub-system level, biologists and computational neural scientists have been somewhat successful at modeling brain regions such as the hippocampus and the auditory nerve system using mathematical models and simplified neuron models such as chaotic attractor and integrate and fire neuron?based neural networks. At the lowest brain system level, biologically and physically realistic brain modelers have used very detailed neuron models (e.g. Hodgkin and Huxley model) to simulate the behavior of small neural networks; however, the very fact that detailed physiologically realistic neuron models were used has made it difficult to build larger neural networks whose behavior could be analyzed properly. Research was carried out in three directions: Invariant learning using the hierarchical, parallel, and distributed organization model of the biological neocortex: a) the invariant recognition of object movement trajectories was investigated; b) the invariant recognition of multiple non-overlapped objects. Chaotic neural network sub-system for image recognition. Detailed biological neuron characteristics: a)the analysis of the mechanisms that allow rhythmic behavior such as in walking using coupled biological neuron oscillators; and b) the analysis of the action potential initiation site within a biological dendrite-neuron-axon structure as well as how the current from an action potential back-propagates into the dendrite. Future work in the neural networks area will include:a) development of a neural system capable of prediction; b) a mathematical model of the rhythmic coupling that occurs in biological neurons; and c)further studies in the structure of the neocortex. Robotics Research in the area of autonomous,intelligent,and interactive robotics for the home or in a work environment is gaining momentum. Research and development work in the areas of bipedal robot real-time control and image processing for object recognition were carried out. The bi-pedal robot that was used is approximately 50cm tall and is equipped with 22 servo motors, a camera, and a 3-axis accelerometer. A pico-size motherboard equipped with a 1 GHz Intel type processor, the Linux operating system with real-time patches, and a notebook PC connected serially to the pico-size motherboard were used for the control of the robot. Close to real-time image recognition was achieved by using two separate processors for image processing and for robot motion control. The notebook PC was used for image processing (OpenCV library) and the pico-size motherboard for robot servomotor control. The image processing data was sent to the motherboard using a serial connection. Bipedal robot locomotion ( fast and slow walk, turn, walking backwards, walking sideways) could be achieved with relative stability using multi-thread processing routines. Balancing in-place on a board that could be tilted in various directions was also achieved. A unicycle robot is being developed. It will be able to balance on one wheel and move autonomously while avoiding obstacles. A new type of robot actuator based on ion movement inside a polymer membrane is being developed. This type of actuator will be lightweight, have no moving mechanical components like gears, and will consume very low power.

Refereed Proceeding Papers

[fujii-01:2008]	R. H. Fujii and T. Hayashi. Learning and Recognition of Similar Temporal Sequences. In 2009 Midwest Symposium on Circuits and System, pages 885–888, Cancun, Mexico, Aug. 2009. IEEE, IEEE Press.
	Learning and recognition of object velocity using a hierarchical network similar in structure to the mammalian neocortex is proposed. Space and time invariant representations of velocity sequences are captured in an unsupervised manner. Recognition of sequences with added noise is achieved.

Unrefereed Papers

[tsuka-01:2008]	T. Yoshida, H. Usui, and T. Tsukahara. An Investigation of a Wireless Receiver Using a Fourier Transform and a Sampling. In The Papers of Technical Meeting on Electronic Circuits. IEE Japan, June 2008.
[tsuka-02:2008]	H. Usui, T. Yoshida, and T. Tsukahara. An Investigation of a Suppressing Method for a Spurious Signal Using a WIF. In The Papers of Technical Meeting on Electronic Circuits. IEE Japan, June 2008.

Books

[tsuka-03:2008]	T. Tsukahara. Nikkei Electronics Tutorial: Introduction to CMOS RF Circuit Design. Nikkei BP, April, June, July, August, Sept. 2008.
	We describe basics on CMOS RF circuit design. The first volume presents RF system design. Then, the second to fourth volumes explain design of on-chip inductors, amplifiers and mixers, and VCOs. Finally, the fifth volume describes design of an low-IF receiver.

Grants

Academic Activities

[tsuka-04:2008]	T. Tsukahara. Commisioned Research Fund from ADVANTEST Corporation, 2008,.
[tsuka-05:2008]	T. Tsukahara. Commisioned Research Fund from Seiko Epson Corporation, 2008.
[tsuka-06:2008]	T. Tsukahara. Cooperative Research Fund from OKI Electric Industry Co., Ltd., 2008.

Ph.D, Master and Bachelor Theses

[tsuka-07:2008]

T. Tsukahara, 2008. Member of the Program Comittee, 2008 IEEE Asian Solid-State Circuits Conference (A-SSCC2008)

[fujii-02:2008]	Taiki Ichishita. Master Thesis: New Paradigm for Invariant Representation of Object Velocity, University of Aizu, 2009. TThesis Advisor : Fujii, R.
[fujii-03:2008]	Taiki Ichishita. Master Thesis: Recurrent Nerural Network Based on Chaotic Neuron, University of Aizu, 2009. Thesis Advisor: Fujii, R.
[fujii-04:2008]	Syuuji Okabe. Graduation Thesis: Neuron Action Potential Initiation and Spread, University of Aizu, 2009. Thesis Advisor: Fujii, R.
[fujii-05:2008]	Mayumi Irifune. Graduation Thesis: Central Pattern Generator, University of Aizu, 2009. Thesis Advisor: Fujii, R.
[fujii-06:2008]	Yudai Nakai. Graduation Thesis: Real-Time Linux and Application for Object Tracking System, University of Aizu, 2009. Thesis Advisor: Fujii, R.
[fujii-07:2008]	Hiroyasu Sato. Graduation Thesis: Embedded Real-Time Operating System for Robotics, University of Aizu, 2009. Thesis Advisor: Fujii, R.
[fujii-08:2008]	Kotaro Umi. Master Thesis: Non-Overlapped Multi-Object Recognition Using Neural Networks, University of Aizu, 2009. Thesis Advisor: Fujii, R.
[fujii-09:2008]	Daisuke Nakatomi. Graduation Thesis: Achieving Stable Walk of a Humanoid Robot, University of Aizu, 2009. Thesis Advisor: Fujii, R.
[tsuka-08:2008]	Hideyuki Ito. Graduation Thesis: A Theoretical Study and a Gain- Boosting Method of RC Poly-Phase Filters, University of Aizu, Feb. 2008. Thesis Advisor: Tsukahara, T.
[tsuka-09:2008]	Masakazu Kuwayama. Graduation Thesis: An Architectural Study of an RF Transmitter with a High-Sideband Rejection Ratio, University of Aizu, Feb. 2008. Thesis Advisor: Tsukahara, T.
[tsuka-10:2008]	Takahiro Sakamoto. Graduation Thesis: An Architectural Study of an Image-Rejection Mixer with a High Image-Rejection Ratio, University of Aizu, Feb. 2008. Thesis Advisor: Tsukahara, T.
[tsuka-11:2008]	Seiya Izumi. Graduation Thesis: Signal Selection and Demodulation Methods Using Fourier Transform for Nyquist-filtered IF Signals, University of Aizu, Feb. 2008. Thesis Advisor: Tsukahara, T.
[tsuka-12:2008]	Takashi Ishizaka. Graduation Thesis: A Higher-order Windowed Integration Filter (WIF) Suitable for a Direct-Digital Frequency Synthesizer, University of Aizu, Feb. 2008. Thesis Advisor: Tsukahara, T.
[tsuka-13:2008]	Kemma Takano. Graduation Thesis: Design of gm-C Complex Bandpass Filters, University of Aizu, Feb. 2008. Thesis Advisor: Tsukahara, T.

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