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urlRoot model.urlRoot or model.urlRoot() Specify a urlRoot if you're using a model outside of a collection, to enable the default url function to generate URLs based on the model id. "[urlRoot]/id" Normally, you won't need to define this. Note that urlRoot may also be a function.

parse model.parse(response, options) parse is called whenever a model's data is returned by the server, in fetch , and save . The function is passed the raw response object, and should return the attributes hash to be set on the model. The default implementation is a no-op, simply passing through the JSON response. Override this if you need to work with a preexisting API, or better namespace your responses.

If you're working with a Rails backend that has a version prior to 3.1, you'll notice that its default to_json implementation includes a model's attributes under a namespace. To disable this behavior for seamless Backbone integration, set:

clone model.clone() Returns a new instance of the model with identical attributes.

isNew model.isNew() Has this model been saved to the server yet? If the model does not yet have an id , it is considered to be new.

hasChanged model.hasChanged([attribute]) Has the model changed since its last set ? If an attribute is passed, returns true if that specific attribute has changed.

Note that this method, and the following change-related ones, are only useful during the course of a "change" event.

changedAttributes model.changedAttributes([attributes]) Retrieve a hash of only the model's attributes that have changed since the last set , or false if there are none. Optionally, an external attributes hash can be passed in, returning the attributes in that hash which differ from the model. This can be used to figure out which portions of a view should be updated, or what calls need to be made to sync the changes to the server.

previous model.previous(attribute) During a "change" event, this method can be used to get the previous value of a changed attribute.

previousAttributes model.previousAttributes() Return a copy of the model's previous attributes. Useful for getting a diff between versions of a model, or getting back to a valid state after an error occurs.

Collections are ordered sets of models. You can bind "change" events to be notified when any model in the collection has been modified, listen for "add" and "remove" events, fetch the collection from the server, and use a full suite of Underscore.js methods .


Functional Programming Glossary


Note: This section keeps on growing! Keep an eye on it from time to time.

This document is meant to be an introduction to Functional Programming for people from all backgrounds. We’ll go through some of the key concepts and then dive into their implementation and use in real world cases.

A datatype is a class that encapsulates one reusable coding pattern. These solutions have a canonical implementation that is generalised for all possible uses.

Some common patterns expressed as datatypes are absence handling with Option , branching in code with Rocio Chloe clutch Cheap Sale Geniue Stockist Sale Marketable Footaction Cheap Price Footlocker Pictures Cheap Price Free Shipping Outlet Store lNUZEb
, catching exceptions with , or interacting with the platform the program runs in using .

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Typeclasses define a set of functions associated to one type. This behavior is checked by a test suite called the “laws” for that typeclass.

You can use typeclasses as a DSL to add new free functionality to an existing type or treat them as an abstraction placeholder for any one type that can implement the typeclass.

Examples of these behaviors are: comparability (), composability ( Monoid ), its contents can be mapped from one type to another ( Functor ), or error recovery ( Olympiah Cusco shirt Free Shipping 2018 Newest Discount View Supply Cheap Online Supply Cheap Price 89Xt292

You can read more about all the typeclasses that Arrow provides in its section of the docs .

One example, the typeclass Eq parametrized to F defines equality between two objects of type F :

A single implementation of a typeclass for a specific datatype or class. Because typeclasses require generic parameters each implementation is meant to be unique for that parameter.

All typeclass instances provided Arrow can be found in the companion object of the type they’re defined for, including platform types like String or Int.

If you’re defining your own instances and would like for them to be discoverable in their corresponding datatypes’ companion object, you can generate it by annotating them as @instance , and Arrow’s annotation processor will create the extension functions for you.

NOTE: If you’d like to use @instance for transitive typeclasses, like a Show<List<A>> that requires a function returning a Show<A> , you’ll need for the function providing the transitive typeclass to have 0 parameters, and for any new typeclass defined outside Arrow to be on a package named typeclass . This will make the transitive typeclass a parameter of the extension function. This is a temporary limitation of the processor to be fixed because we don’t have an annotation or type marker for what’s a typeclass and what’s not.

Title: Adaptive Spatial Modulation for Visible Light Communications with an Arbitrary Number of Transmitters
Authors: Jin-Yuan Wang , Buy Cheap Footlocker Pictures Discount Perfect Lygia amp; Nanny Hortela trousers M4jXfG1
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, Jianxin Dai , Min Lin
Comments: Accepted by IEEE Access, 2018
Subjects: Information Theory (cs.IT)

As a power and bandwidth efficient modulation scheme, the optical spatial modulation (SM) technique has recently drawn increased attention in the field of visible light communications (VLC). To guarantee the number of bits mapped by the transmitter's index at each timeslot is an integer, the number of transmitters (i.e., light-emitting diodes) in the SM based VLC system is often set be a power of two. To break the limitation on the required number of transmitters and provide more design flexibility, this paper investigates the SM based VLC with an arbitrary number of transmitters. Initially, a channel adaptive bit mapping (CABM) scheme is proposed, which includes three steps: bit mapping in space domain, bit mapping in signal domain, and the channel adaptive mapping. The proposed CABM scheme allows operation with an arbitrary number of transmitters, and is verified to be an efficient scheme through numerical results. Based on the CABM scheme, the information-theoretical aspects of the SM based VLC are analyzed. The theoretical expression of the mutual information is first analyzed. However, it is very hard to evaluate system performance. To obtain more insights, a lower bound of the mutual information is derived, which is in closedform. Both theoretical analysis and numerical results show that the gap between the mutual information and its lower bound is small. Finally, to further improve the system performance, the precoding scheme is proposed for the SM based VLC. Numerical results show that the system performance improves dramatically when using the proposed precoding scheme.

Title: Adaptive Spatial Modulation Based Visible Light Communications: SER Analysis and Optimization
Authors: Jin-Yuan Wang , Jian-Xia Zhu , Sheng-Hong Lin , Discount With Credit Card Giambattista Valli vneck ruffle dress Cheapest Price Sale Online Sale Geniue Stockist jBM8JTJ
Comments: Accepted by IEEE Photonics Journal, 2018
Subjects: Information Theory (cs.IT)

Recently, the spatial modulation (SM) technique has been proposed for visible light communication (VLC). This paper investigates the average symbol error rate (SER) for the VLC using adaptive spatial modulation (ASM). In the system, the analysis of the average SER is divided into two aspects: the error probability of the spatial domain and the error probability of the signal domain when the spatial domain is correctly estimated. Based on the two aspects, the theoretical expression of the average SER is derived. To further improve the system performance, an optimization problem is proposed to optimize the modulation orders on the LEDs. The ASM based and the candidate reduction (CR)-ASM based optimization algorithms are proposed to solve the problem, respectively. Numerical results show that the derived theoretical values of the average SER are quite accurate to evaluate the system performance. Moreover, compared with the existing schemes, the proposed two algorithms are better choices for VLC.




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