I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

Principles of Neural Science

A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

http://ieeexplore.ieee.org/iel2/815/3148/00100651.pdf

Robot vision

From the Publisher:
Cynthia Breazeal here presents her vision of the sociable robot of the future, a synthetic creature and not merely a sophisticated tool. A sociable robot will be able to understand us, to communicate and interact with us, to learn from us and grow with us. It will be socially intelligent in a humanlike way. Eventually sociable robots will assist us in our daily lives, as collaborators and companions. Because the most successful sociable robots will share our social characteristics, the effort to make sociable robots is also a means for exploring human social intelligence and even what it means to be human.
Breazeal defines the key components of social intelligence for these machines and offers a framework and set of design issues for their realization. Much of the book focuses on a nascent sociable robot she designed named Kismet. Breazeal offers a concrete implementation for Kismet, incorporating insights from the scientific study of animals and people, as well as from artistic disciplines such as classical animation. This blending of science, engineering, and art creates a lifelike quality that encourages people to treat Kismet as a social creature rather than just a machine. The book includes a CD-ROM that shows Kismet in action.

Designing Sociable Robots

A 1.5-GHz low noise amplifier (LNA), intended for use in a global positioning system (GPS) receiver, has been implemented in a standard 0.6-/spl mu/m CMOS process. The amplifier provides a forward gain (S21) of 22 dB with a noise figure of only 3.5 dB while drawing 30 mW from a 1.5 V supply. In this paper, we present a detailed analysis of the LNA architecture, including a discussion on the effects of induced gate noise in MOS devices.

/pdf/a-1-5-v-1-5-ghz-cmos-low-noise-amplifier-4u1tvhs78n.pdf

A 1.5-V, 1.5-GHz CMOS low noise amplifier

Starting from human ?sense of touch,? this paper reviews the state of tactile sensing in robotics. The physiology, coding, and transferring tactile data and perceptual importance of the ?sense of touch? in humans are discussed. Following this, a number of design hints derived for robotic tactile sensing are presented. Various technologies and transduction methods used to improve the touch sense capability of robots are presented. Tactile sensing, focused to fingertips and hands until past decade or so, has now been extended to whole body, even though many issues remain open. Trend and methods to develop tactile sensing arrays for various body sites are presented. Finally, various system issues that keep tactile sensing away from widespread utility are discussed.

Tactile Sensing—From Humans to Humanoids

The extended gate chemically sensitive field effect transistor as multi-species microprobe☆

This paper reports on the first demonstration of a 1.05-GHz microelectromechanical (MEMS) oscillator based on lateral-field-excited (LFE) piezoelectric AlN contourmode resonators. The oscillator shows a phase noise level of -81 dBc/Hz at 1-kHz offset frequency and a phase noise floor of -146 dBc/Hz, which satisfies the global system for mobile communications (GSM) requirements for ultra-high frequency (UHF) local oscillators (LO). The circuit was fabricated in the AMI semiconductor (AMIS) 0.5-?m complementary metaloxide- semiconductor (CMOS) process, with the oscillator core consuming only 3.5 mW DC power. The device overall performance has the best figure-of-merit (FoM) when compared with other gigahertz oscillators that are based on film bulk acoustic resonator (FBAR), surface acoustic wave (SAW), and CMOS on-chip inductor and capacitor (CMOS LC) technologies. A simple 2-mask process was used to fabricate the LFE AlN resonators operating between 843 MHz and 1.64 GHz with simultaneously high Q (up to 2,200) and kt 2 (up to 1.2%). This process further relaxes manufacturing tolerances and improves yield. All these advantages make these devices suitable for post-CMOS integrated on-chip direct gigahertz frequency synthesis in reconfigurable multiband wireless communications.

/pdf/1-05-ghz-cmos-oscillator-based-on-lateral-field-excited-1ac015y0wc.pdf

1.05-GHz CMOS oscillator based on lateral- field-excited piezoelectric AlN contour- mode MEMS resonators

A CCD imager whose sampling structure is loosely modeled after the biological visual system is described. Its architecture and advantages over conventional cameras for pattern recognition are discussed. The sensor has embedded in its structure a logarithmic transformation that makes it size and rotation invariant. Simulations on real images using the actual sensor geometry have been performed to study the sensor performance for 2D pattern recognition and object tracking.

A Foveated Retina-Like Sensor Using CCD Technology

The objective of voice conversion algorithms is to modify the speech by a particular source speaker so that it sounds as if spoken by a different target speaker. Current conversion algorithms employ a training procedure, during which the same utterances spoken by both the source and target speakers are needed for deriving the desired conversion parameters. Such a (parallel) corpus, is often difficult or impossible to collect. Here, we propose an algorithm that relaxes this constraint, i.e., the training corpus does not necessarily contain the same utterances from both speakers. The proposed algorithm is based on speaker adaptation techniques, adapting the conversion parameters derived for a particular pair of speakers to a different pair, for which only a nonparallel corpus is available. We show that adaptation reduces the error obtained when simply applying the conversion parameters of one pair of speakers to another by a factor that can reach 30%. A speaker identification measure is also employed that more insightfully portrays the importance of adaptation, while listening tests confirm the success of our method. Both the objective and subjective tests employed, demonstrate that the proposed algorithm achieves comparable results with the ideal case when a parallel corpus is available.

/pdf/nonparallel-training-for-voice-conversion-based-on-a-2oehb7itpg.pdf

Nonparallel training for voice conversion based on a parameter adaptation approach

This paper reports on the first demonstration of a reconfigurable complementary-metal-oxide-semiconductor (CMOS) oscillator based on microelectromechanical system (MEMS) resonators operating at four different frequencies (268, 483, 690, and 785 MHz). A bank of multifrequency switchable AlN contour-mode MEMS resonators was connected to a single CMOS oscillator circuit that can be configured to selectively operate in four different states with distinct oscillation frequencies. The phase noise (PN) of the reconfigurable oscillator was measured for each of the four different frequencies of operation, showing values between -94 and - 70 dBc/Hz at a 1-kHz offset and PN floor values as low as -165 dBc/Hz at a 1-MHz offset. Jitter values as low as a 114-fs root mean square (integrated 12 kHz-20 MHz) and switching times as fast as 20 μs were measured. This first prototype represents a miniaturized solution (30 times smaller) over commercially available voltage-controlled surface-acoustic-wave oscillators and potentially has the advantage of generating multiple stable frequencies without the need of cumbersome and power-consuming phase-locked-loop circuits.

J. Van der Spiegel

Papers

The extended gate chemically sensitive field effect transistor as multi-species microprobe☆

1.05-GHz CMOS oscillator based on lateral- field-excited piezoelectric AlN contour- mode MEMS resonators

A Foveated Retina-Like Sensor Using CCD Technology

Nonparallel training for voice conversion based on a parameter adaptation approach

Reconfigurable CMOS Oscillator Based on Multifrequency AlN Contour-Mode MEMS Resonators