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darlington pair amplifier experiments

时间:2021-06-14 00:56:55 来源:网络整理编辑:Allied Components

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Get ready for Thursday’s launch of Verizon iPhone 4

Get ready for Thursday’s launch of Verizon iPhone 4

ToP Technologies Enable all-Ethernet Backhaul

IEEE specification 1588 and ITU-T Synchronous Ethernet (SyncE) are ToP technologies that serve to synchronize clock frequency across devices in the Ethernet backhaul network and improve clock accuracy to satisfy the timing requirements of supporting mobile voice subscribers (i.e., achieve the desired +-50ppb when synchronized to a primary reference clock source).

darlington pair amplifier experiments

SyncE is a technology that achieves frequency synchronization across Ethernet network devices. Synchronous Ethernet offers two major changes over traditional Ethernet to make it suitable for clock distribution:

* A mandated clock accuracy of 4.6ppm

* The ESMC protocol (described in ITU-T G.8264) for clock selection, distribution, management, traceability, and failover. (Requires priority marking of ESMC packets.)

darlington pair amplifier experiments

The basic operation (Fig 5) of SyncE interfaces is to derive the frequency from the received bit stream and pass that information up to the system clock.

darlington pair amplifier experiments

Fig 5: Operation of Synchronous Ethernet

The IEEE 1588 standard specifies the Precision Timing Protocol (PTP), for network synchronization. IEEE 1588 differs from SyncE in 2 fundamental ways:

Constructing an objects/actions matrix lets you visualize the simplicity or complexity of your interactive system's conceptual model. The larger the matrix, the more concepts there are to learn. A tall matrix indicates many objects to master. A wide one indicates many actions to learn. The matrix also illustrates how consistent or inconsistent the conceptual model is – how easy it is for users to transfer what they have learned about one part of the system to another.

A small, dense matrix indicates a design that will be easy to learn: few objects, few actions, and the operations on every type of object are the same (see Fig. 11.3A). For example, the conceptual objects in a simple drawing program would be graphical elements: lines, ellipses, arcs, rectangles, triangles, text labels, etc. The applicable actions on graphical objects would presumably be create, delete, view/edit attributes, move, copy, resize, rotate, flip, etc. The objects/actions matrix for such a simple drawing application would have a row for each object type and a column for each action. All the actions would apply to every object type, so the matrix would be densely packed, like that in Figure 11.3A.

A large, sparse matrix reflects an inconsistent design that will be hard to learn and remember because every conceptual object has different actions (see Fig. 11.3B). Such a design will be hard to learn and remember, no matter what user interface is plastered on it.

A good rule of thumb is to simplify the conceptual model so that the matrix representing it is as small and dense as possible. However, a small matrix reflects limited functionality. Achieving a small matrix is difficult when the application is anything more functional than, say, a simple drawing program, a personal phone directory, or a Web site for looking up postage rates. Consider, for example, the objects and actions an intensive-care patient-monitoring system would have. Even a typical word processing application – e.g., Microsoft Word or Apple Pages – embodies a nontrivial array of conceptual objects and actions.