The emphasis of this book is on real-time application of Synopsys tools, used
to combat various problems seen at VDSM geometries. Readers will be
exposed to an effective design methodology for handling complex, submicron
ASIC designs. Significance is placed on HDL coding styles,
synthesis and optimization, dynamic simulation, formal verification, DFT
scan insertion, links to layout, physical synthesis, and static timing analysis.
At each step, problems related to each phase of the design flow are identified,
with solutions and work-around described in detail. In addition, crucial issues
related to layout, which includes clock tree synthesis and back-end
integration (links to layout) are also discussed at length. Furthermore, the
book contains in-depth discussions on the basics of Synopsys technology
libraries and HDL coding styles, targeted towards optimal synthesis solution.
JXMLEditor is a XML editor developed in Java which is based on the Xerces Java parser. The goal of this editor is to offer some features (tree view, drag & drop, syntax colorizing) to create XML documents easily. Also available as Eclipse Plugin.
RS_latch using vhdl,
When using static gates as building blocks, the most fundamental latch is the simple SR latch, where S and R stand for set and reset. It can be constructed from a pair of cross-coupled NOR (Not OR) logic gates. The stored bit is present on the output marked Q.
Normally, in storage mode, the S and R inputs are both low, and feedback maintains the Q and Q outputs in a constant state, with Q the complement of Q. If S (Set) is pulsed high while R is held low, then the Q output is forced high, and stays high when S returns to low similarly, if R (Reset) is pulsed high while S is held low, then the Q output is forced low, and stays low when R returns to low.
Abtract - We propose a new family of fi lter banks,
named NDFB, that can achieve the directional decomposition
of arbitrary N-dimensional (N ≥ 2) signals with a simple and
effi cient tree-structured construction.
The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported.
