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.

Bus master having burst transfer mode

Abstract: A data processing system having a bus master and a memory which is capable of transferring operands in bursts of m in response to a burst request signal provided by the bus master, the operands being clustered modulo m about a selected access address provided by the bus master, where m is two (2) to the n power, n being an integer and characteristic of the memory. The bus master is adapted to automatically increment, modulo m, a selected set n of the bits of the access address as each operand in the burst is transferred, provided that the memory has indicated that the burst can be continued and less than m operands have been transferred.

Method and apparatus for controlling message delivery to wireless receiver devices

Abstract: A method and apparatus for controlling message delivery to wireless receiver devices can be used for example to condense textual messages intended for a wireless receiver device by abbreviating various words in the message. Thus, a first message addressed to a wireless receiver device (20) is received and stored in a storage medium (14). The received message is then translated into a second message using a pre-defined dictionary associated with the wireless receiver device. The second message is then sent to the wireless receiver device. Thus, the wireless receiver device receives shorter messages conveying the same information as the original message that was to be sent to the wireless receiver device. The translating feature can also be used to code messages or translate messages into a different language.

How it works: a field study of non-technical users interacting with an intelligent system

Abstract: In order to develop intelligent systems that attain the trust of their users, it is important to understand how users perceive such systems and develop those perceptions over time. We present an investigation into how users come to understand an intelligent system as they use it in their daily work. During a six-week field study, we interviewed eight office workers regarding the operation of a system that predicted their managers' interruptibility, comparing their mental models to the actual system model. Our results show that by the end of the study, participants were able to discount some of their initial misconceptions about what information the system used for reasoning about interruptibility. However, the overarching structures of their mental models stayed relatively stable over the course of the study. Lastly, we found that participants were able to give lay descriptions attributing simple machine learning concepts to the system despite their lack of technical knowledge. Our findings suggest an appropriate level of feedback for user interfaces of intelligent systems, provide a baseline level of complexity for user understanding, and highlight the challenges of making users aware of sensed inputs for such systems.

Class of cyclic-based estimators for frequency-offset estimation of OFDM systems

Abstract: We present a new class of blind cyclic-based estimators for carrier frequency-offset and symbol-timing error estimation of orthogonal frequency-division multiplexing (OFDM) systems. The proposed approach exploits the properties of the cyclic prefix subset to reveal the synchronization parameters in the likelihood function of the received vector. A new likelihood function for the joint timing and frequency-offset estimation is derived, which globally characterizes the estimation problem. The resulting probabilistic measure is used to develop three classes of unbiased estimators, namely, maximum-likelihood, minimum variance unbiased, and moment estimator. In comparison to the previously proposed methods, the proposed estimators in this study are computationally and statistically efficient, which makes the estimators more attractive for real-time applications. The performance of the estimators is assessed by simulation for an OFDM system.