Android Application Development for the Intel Platform by Ryan Cohen, Tao Wang

By Ryan Cohen, Tao Wang

The variety of Android units operating on Intel processors has elevated considering that Intel and Google introduced, in overdue 2011, that they'd be operating jointly to optimize destiny models of Android for Intel Atom processors. at the present time, Intel processors are available in Android smartphones and drugs made through many of the best brands of Android units, corresponding to Samsung, Lenovo, and Asus.

The elevate in Android units that includes Intel processors has created a requirement for Android functions optimized for Intel structure: Android software improvement for the Intel® Platform is the suitable creation for software program engineers and cellular app builders. via well-designed app samples, code samples and case experiences, the ebook teaches Android software improvement according to the Intel platform—including for smartphones, capsules, and embedded devices—covering functionality tuning, debugging and optimization.

This booklet is together constructed for person studying through Intel software program university and China Shanghai JiaoTong University.

What you’ll learn

Comprehensive creation to the Intel ® Embedded and cellular platform
Android app GUI layout rules and guidelines
Covers the newest Intel Android improvement instruments, together with Intel Beacon Mountain model 0.6 and the Intel Compiler
NDK and C/C++ optimization
Designing and optimizing for low-power consumption
Who this e-book is for

The booklet is basically for app builders, software program engineers and open-source programming fanatics, yet is usually utilized by for education courses and Codeacademy-style courses.

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A little further thought then tells us that since 0 = (1 − 1) = (1 we have the additive inverse u† = −1 u u) ⊕ (−1 u. 2 We usually say this much simpler. The set of objects V is a vector space over its scalar field if there are two operations which we denote by u + v and cu which generate new objects in the vector space for any u, v and scalar c. We then just add that these operations satisfy the usual commutative, associative and distributive laws and there are unique additive inverses. 3 The objects are often called vectors and sometimes we denote them by u although this notation is often too cumbersome.

This is called the L2 norm of f . It is possible to prove the Cauchy–Schwartz inequality in this more general setting also. 1 (General Cauchy–Schwartz Inequality) If V is an inner product space with inner product < , > and induced norm || ||, then | < u, v > | ≤ ||u|| ||v|| with equality occurring if and only if u and v are linearly dependent. Proof The proof is different than the one you would see in a Calculus text for of course, and is covered in a typical course on beginning analysis. 3 We can use the Cauchy–Schwartz inequality to define a notion of angle between objects exactly like we would do in 2 .

Fig. 10: Draw2DGSO: drawing the vectors 5 10 15 20 f u n c t i o n Draw2DGSO( V1 , V2) % T = linspace (0 ,1 ,2) ; h o l d on % find equation of l i n e for i f V1 ( 1 ) == 0 f 1 = @( t ) t ; else f 1 = @( t ) (V1 ( 2 ) /V1 ( 1 ) ) ∗ t end T = [ 0 : V1 ( 1 ) : V1 ( 1 ) ] ; p l o t (T , f 1 (T) ) ; t e x t ( V1 ( 1 ) / 2 ,V1 ( 2 ) / 2 , ’V1 ’ ) % find equation of l i n e for i f V2 ( 1 ) == 0 f 2 = @( t ) t ; else f 2 = @( t ) (V2 ( 2 ) /V2 ( 1 ) ) ∗ t end p l o t (T , f 2 (T) ) ; T = [ 0 : V2 ( 1 ) : V2 ( 1 ) ] ; t e x t ( V2 ( 1 ) / 2 ,V2 ( 2 ) / 2 , ’V2 ’ ) hold o f f end v e c t o r V1 ; ; v e c t o r V2 ; ; Note we also use the new text command to add text at desired points in the graph.

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