Merge pull request #22 from majianjia/dev

update docs

README.md

@@ -1,5 +1,6 @@
 
 # Neural Network on Microcontroller (NNoM)
+[![Build Status](https://travis-ci.org/majianjia/nnom.svg?branch=master)](https://travis-ci.org/majianjia/nnom)
 
 NNoM is a higher-level layer-based Neural Network library specifically for microcontrollers. 
 
@@ -21,12 +22,10 @@ Guides:
 
 Examples:
 
-[RT-Thread-MNIST example (中文)](https://majianjia.github.io/nnom/example_mnist_simple_cn/)
-
 [MNIST-DenseNet example](examples/mnist-densenet)
 
+[RT-Thread-MNIST example (中文)](https://majianjia.github.io/nnom/example_mnist_simple_cn/)
 
----
 
 ## Why NNoM?
 The aims of NNoM is to provide a light-weight, user-friendly and flexible interface for fast deploying.
@@ -40,11 +39,14 @@ Nowadays, neural networks are **wider**, **deeper**, and **denser**.
 >[3] Huang, G., Liu, Z., Van Der Maaten, L., & Weinberger, K. Q. (2017). Densely connected convolutional networks. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 4700-4708).
 
 
-If you would like to try those more up-to-date, decent and complex structures on MCU
+After 2014, the development of Neural Networks are more focus on structure optimising to improve efficiency and performance, which is more important to the small footprint platforms such as MCUs. 
+However, the available NN libs for MCU are too low-level which make it sooooo difficult to use with these complex strucures. 
+Therefore, we build the NNoM to help developers to manage the structures, memory and parameters, even with the automatic tools for fast deploying. 
+
+Now with NNoM, you are free to play with these more up-to-date, decent and complex structures on MCU. 
 
-NNoM can help you to build them with only a few lines of C codes, same as you did with Python in [**Keras**](https://keras.io/)
+With [**Keras**](https://keras.io/) and our tools, deploying a model only takes a few line of codes, please do check the [examples](examples/).
 
----
 
 ## Available Operations
 
@@ -66,7 +68,7 @@ NNoM can help you to build them with only a few lines of C codes, same as you di
 
 **Activations**
 
-Activation can be used by itself as layer, or can be attached to the previous layer as ["actail"](docs/A%20Temporary%20Guide%20to%20NNoM.md#addictionlly-activation-apis) to reduce memory cost.
+Activation can be used by itself as layer, or can be attached to the previous layer as ["actail"](docs/A_Temporary_Guide_to_NNoM.md#addictionlly-activation-apis) to reduce memory cost.
 
 | Actrivation | Status |Layer API|Activation API|Comments|
 | ------ |-- |--|--|--|
@@ -95,20 +97,20 @@ Activation can be used by itself as layer, or can be attached to the previous la
 | Substraction  | Beta|Sub()||
 | Dot  | Under Dev. |||
 
----
+
 
 ## Dependencies
 
 NNoM now use the local pure C backend implementation by default. Thus, there is no special dependency needed. 
 
----
+
 
 ## Optimization
 You can select [CMSIS-NN/DSP](https://github.com/ARM-software/CMSIS_5/tree/develop/CMSIS/NN) as the backend for about 5x performance with ARM-Cortex-M4/7/33/35P. 
 
 Check [Porting and optimising Guide](docs/Porting_and_Optimisation_Guide.md) for detail. 
 
----
+
 
 ## Contacts
 Jianjia Ma