Motorola

About: Motorola is a company organization based out in Schaumburg, Illinois, United States. It is known for research contribution in the topics: Signal & Communications system. The organization has 27298 authors who have published 38274 publications receiving 968710 citations. The organization is also known as: Motorola, Inc. & Galvin Manufacturing Corporation.

Digital radio frequency receiver

Abstract: A digital radio receiver is described. The digital receiver of the present invention contemplates a digital radio receiver which operates on a received analog signal which has been converted to a digital form after preselection at the output of the antenna. The digital receiver of the present invention comprises a preselector, a high-speed analog-to-digital (A/D) converter, a digitally implemented intermediate-frequency (IF) selectivity section having an output signal at substantially baseband frequencies, and digital signal processor (DSP) circuit performing demodulation and audio filtering. The radio architecture of the present invention is programmably adaptable to virtually every known modulation scheme and is particularly suitable for implementation on integrated circuits.

Using pressure differences with a touch-sensitive display screen

Abstract: Disclosed is a user interface that responds to differences in pressure detected by a touch-sensitive screen. The user selects one type of user-interface action by “lightly” touching the screen and selects another type of action by exerting more pressure. Embodiments can respond to single touches, to gestural touches that extend across the face of the touch-sensitive screen, and to touches in which the user-exerted pressure varies during the course of the touch. Some embodiments respond to how quickly the user changes the amount of pressure applied. In some embodiments, the location and pressure of the user's input are compared against a stored gesture profile. Action is taken only if the input matches “closely enough” to the stored gesture profile. In some embodiments, a notification is sent to the user when the pressure exceeds a threshold between a light and a heavy press.

Method for making semiconductor device having no die supporting surface

Abstract: A wire bondable plastic encapsulated semiconductor device (58) having no die supporting surface can be manufactured. In one embodiment, a semiconductor die (22) and a plurality of conductors (12) extending toward the periphery of the die are provided. The die is rigidly held in place on a workholder (60) with a vacuum (62) for the wire bonding process. Wire bonds (26) electrically connect the die to the conductors. The wire bonded die is then placed inside a mold cavity (64), and a resin encapsulated is transferred into the cavity under elevated temperature and pressure to form package body (70) around the die, the wire bonds and a portion of the conductors. Before the package body is formed, the die is supported solely by the the rigidity of the wire bonds since there is no die supporting surface connected to the conductors.

Distributed computer system with network and resource status monitoring

Abstract: A requesting manager sends a message to its local configuration processor requesting notice of status changes in a general or particular, resource or node. The configuration manager establishes a record in its status monitoring file containing the information from the requesting process' message. The configuration manager receives messages: from remote configuration managers or local resource managers regarding resource status changes; and from its local network interface module regarding node changes. The configuration manager then compares these status change notifications with the records in its status monitoring file. If there is a match, the configuration manager sends a message to the requesting process reporting the status change. The status changes that are reported may be limited by the requesting process by specifying a particular status change, a particular resource, or other option.

Machine Learning in Medical Imaging

Abstract: This article will discuss very different ways of using machine learning that may be less familiar, and we will demonstrate through examples the role of these concepts in medical imaging. Although the term machine learning is relatively recent, the ideas of machine learning have been applied to medical imaging for decades, perhaps most notably in the areas of computer-aided diagnosis (CAD) and functional brain mapping. We will not attempt in this brief article to survey the rich literature of this field. Instead our goals will be 1) to acquaint the reader with some modern techniques that are now staples of the machine-learning field and 2) to illustrate how these techniques can be employed in various ways in medical imaging.